{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Chapater 2 Code - Python 3 version"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### abaloneCorrHeat.py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                  Length  Diameter    Height  Whole weight  Shucked weight  \\\n",
      "Length          1.000000  0.986812  0.827554      0.925261        0.897914   \n",
      "Diameter        0.986812  1.000000  0.833684      0.925452        0.893162   \n",
      "Height          0.827554  0.833684  1.000000      0.819221        0.774972   \n",
      "Whole weight    0.925261  0.925452  0.819221      1.000000        0.969405   \n",
      "Shucked weight  0.897914  0.893162  0.774972      0.969405        1.000000   \n",
      "Viscera weight  0.903018  0.899724  0.798319      0.966375        0.931961   \n",
      "Shell weight    0.897706  0.905330  0.817338      0.955355        0.882617   \n",
      "Rings           0.556720  0.574660  0.557467      0.540390        0.420884   \n",
      "\n",
      "                Viscera weight  Shell weight     Rings  \n",
      "Length                0.903018      0.897706  0.556720  \n",
      "Diameter              0.899724      0.905330  0.574660  \n",
      "Height                0.798319      0.817338  0.557467  \n",
      "Whole weight          0.966375      0.955355  0.540390  \n",
      "Shucked weight        0.931961      0.882617  0.420884  \n",
      "Viscera weight        1.000000      0.907656  0.503819  \n",
      "Shell weight          0.907656      1.000000  0.627574  \n",
      "Rings                 0.503819      0.627574  1.000000  \n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fd5f9717630>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "__author__ = 'mike_bowles'\n",
    "import pandas as pd\n",
    "from pandas import DataFrame\n",
    "import matplotlib.pyplot as plot\n",
    "%matplotlib inline\n",
    "\n",
    "target_url = (\"http://archive.ics.uci.edu/ml/machine-\"\n",
    "              \"learning-databases/abalone/abalone.data\")\n",
    "#read abalone data\n",
    "abalone = pd.read_csv(target_url,header=None, prefix=\"V\")\n",
    "abalone.columns = ['Sex', 'Length', 'Diameter', 'Height',\n",
    "                   'Whole weight', 'Shucked weight',\n",
    "                   'Viscera weight', 'Shell weight', 'Rings']\n",
    "\n",
    "#calculate correlation matrix\n",
    "corMat = DataFrame(abalone.iloc[:,1:9].corr())\n",
    "#print correlation matrix\n",
    "print(corMat)\n",
    "\n",
    "#visualize correlations using heatmap\n",
    "plot.pcolor(corMat)\n",
    "plot.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "\n",
    "\n",
    "### abaloneParallelPlot.py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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gPKmrGbtj1mYH9Q7JJGQ2WR4aVI4H6HqGObrGZJyxlhEuK9GmCm1eTBquTM+/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8EUselg19pnPKmRukD3HbptCZsGFxVfWEGceWm89hjQZiBuBxRBs9Ku43AAdiNxv0czZwaWlYEY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\nH06voJ9MoMiaAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f1ee6f465c0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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VaWkZdgQ/8bkM5yT//JUE3VTgWxwZkazoxS1f/JEt6trx5qFEiwRhC4rG0okr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\nbIcpx9HosAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f1ee3a0c9b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "__author__ = 'mike_bowles'\n",
    "import pandas as pd\n",
    "from pandas import DataFrame\n",
    "import matplotlib.pyplot as plot\n",
    "from math import exp\n",
    "target_url = (\"http://archive.ics.uci.edu/ml/machine-\"\n",
    "              \"learning-databases/abalone/abalone.data\")\n",
    "#read abalone data\n",
    "abalone = pd.read_csv(target_url,header=None, prefix=\"V\")\n",
    "abalone.columns = ['Sex', 'Length', 'Diameter', 'Height',\n",
    "                   'Whole Wt', 'Shucked Wt',\n",
    "                   'Viscera Wt', 'Shell Wt', 'Rings']\n",
    "#get summary to use for scaling\n",
    "summary = abalone.describe()\n",
    "minRings = summary.iloc[3,7]\n",
    "maxRings = summary.iloc[7,7]\n",
    "nrows = len(abalone.index)\n",
    "\n",
    "for i in range(nrows):\n",
    "    #plot rows of data as if they were series data\n",
    "    dataRow = abalone.iloc[i,1:8]\n",
    "    labelColor = (abalone.iloc[i,8] - minRings) / (maxRings - minRings)\n",
    "    dataRow.plot(color=plot.cm.RdYlBu(labelColor), alpha=0.5)\n",
    "\n",
    "plot.xlabel(\"Attribute Index\")\n",
    "plot.ylabel((\"Attribute Values\"))\n",
    "plot.show()\n",
    "\n",
    "#renormalize using mean and standard variation, then compress\n",
    "# with logit function\n",
    "\n",
    "meanRings = summary.iloc[1,7]\n",
    "sdRings = summary.iloc[2,7]\n",
    "\n",
    "for i in range(nrows):\n",
    "    #plot rows of data as if they were series data\n",
    "    dataRow = abalone.iloc[i,1:8]\n",
    "    normTarget = (abalone.iloc[i,8] - meanRings)/sdRings\n",
    "    labelColor = 1.0/(1.0 + exp(-normTarget))\n",
    "    dataRow.plot(color=plot.cm.RdYlBu(labelColor), alpha=0.5)\n",
    "\n",
    "plot.xlabel(\"Attribute Index\")\n",
    "plot.ylabel((\"Attribute Values\"))\n",
    "plot.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### abaloneSummary.py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  Sex  Length  Diameter  Height  Whole weight  Shucked weight  Viscera weight  \\\n",
      "0   M   0.455     0.365   0.095        0.5140          0.2245          0.1010   \n",
      "1   M   0.350     0.265   0.090        0.2255          0.0995          0.0485   \n",
      "2   F   0.530     0.420   0.135        0.6770          0.2565          0.1415   \n",
      "3   M   0.440     0.365   0.125        0.5160          0.2155          0.1140   \n",
      "4   I   0.330     0.255   0.080        0.2050          0.0895          0.0395   \n",
      "\n",
      "   Shell weight  Rings  \n",
      "0         0.150     15  \n",
      "1         0.070      7  \n",
      "2         0.210      9  \n",
      "3         0.155     10  \n",
      "4         0.055      7  \n",
      "     Sex  Length  Diameter  Height  Whole weight  Shucked weight  \\\n",
      "4172   F   0.565     0.450   0.165        0.8870          0.3700   \n",
      "4173   M   0.590     0.440   0.135        0.9660          0.4390   \n",
      "4174   M   0.600     0.475   0.205        1.1760          0.5255   \n",
      "4175   F   0.625     0.485   0.150        1.0945          0.5310   \n",
      "4176   M   0.710     0.555   0.195        1.9485          0.9455   \n",
      "\n",
      "      Viscera weight  Shell weight  Rings  \n",
      "4172          0.2390        0.2490     11  \n",
      "4173          0.2145        0.2605     10  \n",
      "4174          0.2875        0.3080      9  \n",
      "4175          0.2610        0.2960     10  \n",
      "4176          0.3765        0.4950     12  \n",
      "            Length     Diameter       Height  Whole weight  Shucked weight  \\\n",
      "count  4177.000000  4177.000000  4177.000000   4177.000000     4177.000000   \n",
      "mean      0.523992     0.407881     0.139516      0.828742        0.359367   \n",
      "std       0.120093     0.099240     0.041827      0.490389        0.221963   \n",
      "min       0.075000     0.055000     0.000000      0.002000        0.001000   \n",
      "25%       0.450000     0.350000     0.115000      0.441500        0.186000   \n",
      "50%       0.545000     0.425000     0.140000      0.799500        0.336000   \n",
      "75%       0.615000     0.480000     0.165000      1.153000        0.502000   \n",
      "max       0.815000     0.650000     1.130000      2.825500        1.488000   \n",
      "\n",
      "       Viscera weight  Shell weight        Rings  \n",
      "count     4177.000000   4177.000000  4177.000000  \n",
      "mean         0.180594      0.238831     9.933684  \n",
      "std          0.109614      0.139203     3.224169  \n",
      "min          0.000500      0.001500     1.000000  \n",
      "25%          0.093500      0.130000     8.000000  \n",
      "50%          0.171000      0.234000     9.000000  \n",
      "75%          0.253000      0.329000    11.000000  \n",
      "max          0.760000      1.005000    29.000000  \n"
     ]
    },
    {
     "data": {
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fSnwvgBGnoTYzs9o3XNPQRenTs/ZclUxSa1WjMjOzzJRzH8H/LbPMzMzq0HB9BH8BHArs\nt8eSlZOA/TOIzczMMjBcH8EZwHuBw0j6CQqJ4DngyuqGZWZmWRmuj+B2Sf8LmBcRd2QYk5mZZWjY\nPoKIGMCriJmZjWvldBbfL+nDkg6X1F54VD0yMzPLRDnrEVyYfr2kqMxTTJiZjRPlzD7qqSbMzMax\nshavl9QJHAUM3kgWEV+sVlBmZpadEROBpKuBU0gSwSrgLJLFaZwIzMzGgXI6i88lWZTm9xFxAfBa\nYGJVozIzGwfa29uRVNYDKGu/9vbKj9Upp2noTxExIGmnpEkki9S4o9jMbATbtm0jIip6zELSqKRy\nEsEaSZOBW0kWq3kB+HHFIzEzs1yUM2ro/enTZZLuASZFxPqRXifpNuDNwFMR0ZmWtQNfBmYAjwJ/\nGxHb9i10MzOrhBH7CCSdXHgA04HJ6fORfAE4c4+yjwIPRMQrgQfSbTMzy1E5TUP/teh5K3A8SRPR\nsAvTRMSDkmbsUfxWkhFIALcD3wMWlhGDmZlVSTlNQ/+peFvS4cB/38fzHRIRT6bHfVLSwft4HDMz\nq5Byho/u6XGgs9KB7EnSRZLWSFqzZcuWap/OzKxhlXND2VKSuYUgSRyzgZ/u4/n+IGlaWhuYRjIU\ntaSIWA4sB+jq6qrs+CszMxtU1vDRouc7gZ6I+Jd9PN+3gPcAn0q/fnMfj2NmZhVSTiL4KnBk+vwX\nEfFSOQeW1EPSMXyQpMeBq0kSwFckzQceA94+6ojNzKyihluzuAX4H8C7Scb8NwEHS1oaEZ+SdExE\nPDTU6yNi3hDfOnUM8ZqZWYUNVyP4J5JF6mdExPMA6RQT10u6heQeAU9RbWZW54ZLBGcDr4yiiTIi\n4jlJFwNPk8xCamZmdW64RDAQJWZLiohdkrZExA+rGJeZWd2LqyfBNa+o/DErbLhE8DNJf7fnAjSS\n3gVsqngkZmbjjD7+XFVmH41rKnrIYRPBJcDXJV1IMqVEAH8D7Ae8rbJhmJlZXoZMBBHxO+B1kuYC\nHYCAuyPigayCMzOz6itnrqHVwOoMYjEzsxzsy1xDZmY2jpRzZ7GZme2jSi8t2dbWVtHjgROBmVnV\njGbEkKSKjzAql5uGzMwanBOBmVmDcyIwM2twTgRmZg3OicDMrME5EZiZNTgnAjOzBudEYGbW4JwI\nzMwanBOBmVmDcyIwM2twTgRmZg3OicDMrME5EZiZNTgnAjOzBpfLegSSHgWeB3YBOyOiK484zMws\n34Vp5kTE0zme38zMcNOQmVnDyysRBHCfpLWSLsopBjMzI7+moRMj4glJBwP3S/p5RDxYvEOaIC4C\nmD59eh4xmpk1hFxqBBHxRPr1KeAu4PgS+yyPiK6I6Jo6dWrWIZqZNYzME4GkAyS9vPAcOB3YkHUc\nZmaWyKNp6BDgLkmF86+MiHtyiMPMzMghEUTEr4HXZn1eMzMrzcNHzcwanBOBmVmDy/POYjOzhpT2\nkZZVHhHVDseJwMwsa1lc3EfDTUNmZg3ONQIzsxzl1RxUzDUCM7OcFJKAJO65557dtrPkRGDjXnd3\nN62trUiitbWV7u7uvEMyGySJgYEBzjjjDAYGBjJPAuBEYONcd3c3N998M5MnT0YSkydP5uabb3Yy\nsJpx9913D7udBdVa73UpXV1dsWbNmrzDsDrU0tLCzp079yqfMGEC/f39OURk9meSBmsEBU1NTURE\nRfoJJK0tZwVI1whsXCuVBIYrN8taRNDU1MS99947mASy5kRgZpaTwkU/IjjzzDN3286SE4E1hAMP\nPJC1a9dy4IEH5h2K2W5WrlxJR0cHTU1NdHR0sHLlysxj8H0E1hBeeukljjvuOFpaWvIOxWxQT08P\nixYtYsWKFZx00kn09fUxf/58AObNm5dZHO4stnFptEPw6uF9YONPZ2cnS5cuZc6cOYNlvb29dHd3\ns2HD2NfrKrez2InAxrXhEkI9/O/b+Nbc3Mz27dt3q6n29/fT2trKrl27xnx8jxoyAyZOnDiq8jz1\n9PTQ2dlJc3MznZ2d9PT05B2SVdmsWbPo6+vbrayvr49Zs2ZlGocTgY1r27dv3+uiP3HiRLZv355T\nRKX19PRw/vnns3HjRgYGBti4cSPnn3++k8E4t2jRIubPn09vby/9/f309vYyf/58Fi1alG0ghRsX\navlx3HHHhdWmlStXRkdHRzQ1NUVHR0esXLky75CGlPy716ampqYA9no0NTXlHZpVWTXfQ8CaKOMa\n6xqB7bPCiIelS5eyfft2li5dyqJFi/wpdh8U31laTrmNzE1to1BOtsj74RpBbero6IjVq1fvVrZ6\n9ero6OjIKaLhUcM1AopqATfddNNu2zZ6K1euDEm7/R4l1VyNdeXKlTFz5sxYvXp17NixI1avXh0z\nZ86sWJyUWSPI/SJfzsOJoDY1NTXFjh07divbsWNH5s0ZbW1tJZtVxvJoa2vL9GconLf4glCriaAe\nmgPrpamt2h+myk0EHj5q+6yzs5NzzjmHb3zjG2zatIlZs2YNbldiDHS5JFHp/+NqHHOo84xG3u/X\nnp4ezjvvvL3KV65cmekNUCOpl2HDtTJ8tCHuLB7Nm62W/klq3Zw5c7juuuu47rrrWLBgAcuWLWPh\nwoUsWLAg0zji6klwzSsqf8wMFP7f6uXCVSoJFMprKREUdHR0sGrVKs4++2w2btyYdzh7KQwfLb6h\nLI/ho7k3+5TzqEbTEDVW5WaUTRe1oKOjI2bOnLlbXDNnzsy8j6Aav4+sf8e1/rcuKMR08cUXx7PP\nPhsXX3xxTcdZ601ttdJHkEvTkKQzgc8AzcDnIuJTw+1fdtNQhT8V/vm4/16d4w6jFtYxHUkhxosv\nvphPfvKTXHHFFdxyyy1AtrHWS9NQe3s727Ztq+gx29ra2Lp1a0WPORxJdHZ28sgjjwyWveY1r2HD\nhg018f9Zj7X/np4eFi9ePNi8umjRoorVrmp2iglJzcAvgTcBjwM/AeZFxM+Gek25iaAaS7xV5Y02\nThJWrTRn1MvfvV4S1lDnKVctXGBr5X8zb7WcCN4AXBMRZ6TbVwBExCeHek2lOosL/xwRMfgGKi7L\nSr1cuEqpt87NYlldNIdUJx8A6qbmUo3fZw61/2qq5c7iQ4HfFm0/Dryumifc8+JV2C4uzzIhlDpH\nTV5gS7zRRt2JWurNOs7ebOXSx5+r+DHb2trYek1lj7n1g7uASneWj30EzJ4q/fusxu+yXuSRCEpd\n8fa6qkm6CLgIYPr06WM6YeGiWepin0eNoJSRYsolzhIX7JpMWCUMFedQ5f4AUGSMf/es/uZj/X3m\n/Z6vJXlMMfE4cHjR9mHAE3vuFBHLI6IrIrqmTp1a0QAkce6551aliaaSJDF37tyairN4pEFBqRrW\nnvtkrZyREqV+Fsc59jjzVC9x1po8EsFPgFdKminpZcA7gW9lceLiP/6dd95ZsrwWFC9V19vbW7K8\nlkQEN910U839Hs2sPJkngojYCXwAuBfYBHwlIjK706MePhnMmzev5DqmtXbDTvHv7pJLLilZbma1\nz1NMmJmNU16hzMzMyuJEYGbW4JwIzMwanBOBmVmDcyIwM2twdTFqSNIWYHOFD3sQ8HSFj1kNjrNy\n6iFGcJyV1shxHhERI96RWxeJoBokrSlnWFXeHGfl1EOM4DgrzXGOzE1DZmYNzonAzKzBNXIiWJ53\nAGVynJVTDzGC46w0xzmChu0jMDOzRCPXCMzMjAZMBJJuk/SUpA15xzIUSYdL6pW0SdJGSR/KO6ZS\nJLVK+rGkn6ZxfjzvmIYjqVnSQ5K+nXcsQ5H0qKRHJD0sqWZnWpQ0WdLXJP08/T99Q94x7UnSq9Lf\nY+HxnKRL845rT5L+IX3/bJDUI6k18xgarWlI0snAC8AXI6Iz73hKkTQNmBYR6yS9HFgLnBMRP8s5\ntN0oWYnmgIh4QVIL0Ad8KCJ+mHNoJUm6DOgCJkXEm/OOpxRJjwJdEVHT494l3Q78ICI+l64rsn9E\nPJt3XEOR1Az8DnhdRFT6nqR9JulQkvfNURHxJ0lfAVZFxBeyjKPhagQR8SBQ/VXexyAinoyIdenz\n50nWbTg036j2FokX0s2W9FGTnywkHQb8R+BzecdS7yRNAk4GVgBExI5aTgKpU4F/q6UkUGQCsJ+k\nCcD+lFixsdoaLhHUG0kzgGOAH+UbSWlpc8vDwFPA/RFRk3ECnwY+AgzkHcgIArhP0tp03e5a9FfA\nFuDzaVPb5yQdkHdQI3gn0JN3EHuKiN8B1wOPAU8C/x4R92UdhxNBDZN0IHAncGlEPJd3PKVExK6I\nmE2y9vTxkmquuU3Sm4GnImJt3rGU4cSIOBY4C7gkbcqsNROAY4FbIuIY4EXgo/mGNLS06eotwFfz\njmVPktqAtwIzgb8EDpD0rqzjcCKoUWmb+53AHRHx9bzjGUnaNPA94MycQynlROAtafv7l4C5kv53\nviGVFhFPpF+fAu4Cjs83opIeBx4vqv19jSQx1KqzgHUR8Ye8AynhNOA3EbElIvqBrwMnZB2EE0EN\nSjthVwCbIuKGvOMZiqSpkianz/cj+af+eb5R7S0iroiIwyJiBkkTweqIyPxT10gkHZAODiBtajkd\nqLnRbRHxe+C3kl6VFp0K1NRAhj3MowabhVKPAa+XtH/6vj+VpE8wUw2XCCT1AP8KvErS45Lm5x1T\nCScC7yb55FoY+nZ23kGVMA3olbQe+AlJH0HNDs2sA4cAfZJ+CvwY+E5E3JNzTEPpBu5I//azgSU5\nx1OSpP2BN5F80q45aa3qa8A64BGSa3Lmdxg33PBRMzPbXcPVCMzMbHdOBGZmDc6JwMyswTkRmJk1\nOCcCM7MG50RgdUfS2ySFpFcXlc2QdF7R9uzhhtxK6pL02fT5NZI+PMoYLk2HJo7mNV+QdO4oX/Oo\npING8xqz0XIisHo0j2TGxncWlc0Azivang2UTASSJkTEmoj44BhiuJRkgjCzuudEYHUlnX/pRGA+\nuyeCTwH/Ib35biHwCeAd6fY70k/9yyXdB3xR0il7rEvwWkmrJf1K0vvSc+22j6T/Kem9kj5IMi9M\nr6Te9HunS/pXSeskfTWNc7if41FJH0/3f6RQu5E0RdJ96WRu/wyo6DXvUrL+w8OS/jmd8O+INOaD\nJDVJ+oGk0/f9N2yNyInA6s05wD0R8Utgq6TCHDcfJZkff3ZEXAdcBXw53f5yus9xwFsj4ry9D8vR\nJNNUvwG4StJfDhVARHyWZKrgORExJ226+UfgtHTCuDXAZWX8LE+n+98CFJqmrgb60sncvgVMB5A0\nC3gHyaR0s4FdwPnptMrXAcuAy4Gf5TF7pdW3CXkHYDZK80imlIZkArl5JLfnl+NbEfGnIb73zfR7\nf0o/5R8PlDvH/uuBo4B/SaaL4WUk05iMpDDtwVrgP6fPTy48j4jvSNqWlp9Kksh+kp5jP5Kpv0kX\nh3k7sICkScxsVJwIrG5ImgLMBTolBdAMhKSPlHmIF4f53p5zrQSwk91rzUMtISiSeZbmlRlHwUvp\n113s/l4sNe+LgNsj4oq9vpF0Wh+Wbh4IPD/KOKzBuWnI6sm5JEuMHhERMyLicOA3wEkkF7+XF+27\n5/ZI3qpkDeYpwCkkk+htBo6SNFHSK0g+lZc6/g+BEyUdCcmFWdJfj/7HA+BB4Pz0OGcBbWn5A8C5\nkg5Ov9cu6Yj0e9cBd5A0h926j+e1BuZEYPVkHskc/cXuJBkttB7YKemnkv4B6CW5iD8s6R1lHPvH\nwHdILurXRsQTEfFb4Cvpse8AHirafzlwt6TeiNgCvBfoSWfj/CHwavbNx4GTJa0jmYb6MYB0vep/\nJFm9bD1wPzBN0huBvwGui4g7gB2SLtjHc1uD8uyjZmYNzjUCM7MG50RgZtbgnAjMzBqcE4GZWYNz\nIjAza3BOBGZmDc6JwMyswTkRmJk1uP8PCqbKbhGG3BYAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f1ee416f978>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f1ee43e5fd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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EfCrD45uZWR/jcpSRmZkdLsuCsELSE5LukDQlwxxmZkYRC4Kk/ytp8wC384HP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\nmQHwXzUrBdLc8aO8AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f1ee43d6908>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "__author__ = 'mike_bowles'\n",
    "import pandas as pd\n",
    "from pandas import DataFrame\n",
    "from pylab import *\n",
    "import matplotlib.pyplot as plot\n",
    "\n",
    "target_url = (\"http://archive.ics.uci.edu/ml/machine-\"\n",
    "              \"learning-databases/abalone/abalone.data\")\n",
    "#read abalone data\n",
    "abalone = pd.read_csv(target_url,header=None, prefix=\"V\")\n",
    "abalone.columns = ['Sex', 'Length', 'Diameter', 'Height', 'Whole weight',\n",
    "                   'Shucked weight', 'Viscera weight', 'Shell weight',\n",
    "                   'Rings']\n",
    "\n",
    "\n",
    "print(abalone.head())\n",
    "print(abalone.tail())\n",
    "\n",
    "#print summary of data frame\n",
    "summary = abalone.describe()\n",
    "print(summary)\n",
    "\n",
    "#box plot the real-valued attributes\n",
    "#convert to array for plot routine\n",
    "array = abalone.iloc[:,1:9].values\n",
    "boxplot(array)\n",
    "plot.xlabel(\"Attribute Index\")\n",
    "plot.ylabel((\"Quartile Ranges\"))\n",
    "show()\n",
    "\n",
    "#the last column (rings) is out of scale with the rest\n",
    "# - remove and replot\n",
    "array2 = abalone.iloc[:,1:8].values\n",
    "boxplot(array2)\n",
    "plot.xlabel(\"Attribute Index\")\n",
    "plot.ylabel((\"Quartile Ranges\"))\n",
    "show()\n",
    "\n",
    "#removing is okay but renormalizing the variables generalizes better.\n",
    "#renormalize columns to zero mean and unit standard deviation\n",
    "#this is a common normalization and desirable for other operations\n",
    "# (like k-means clustering or k-nearest neighbors\n",
    "abaloneNormalized = abalone.iloc[:,1:9]\n",
    "\n",
    "\n",
    "for i in range(8):\n",
    "    mean = summary.iloc[1, i]\n",
    "    sd = summary.iloc[2, i]\n",
    "    abaloneNormalized.iloc[:,i:(i + 1)] = (\n",
    "                    abaloneNormalized.iloc[:,i:(i + 1)] - mean) / sd\n",
    "\n",
    "array3 = abaloneNormalized.values\n",
    "boxplot(array3)\n",
    "plot.xlabel(\"Attribute Index\")\n",
    "plot.ylabel((\"Quartile Ranges - Normalized \"))\n",
    "show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### classifierExamplePlot.py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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tVHHdN16xiWZjtpAtHRRWLvy/e+wCs40eU8Ml/sZDe28ICLCS29Dh8PTwDXfg\nKxf+Ow2tPHJkihcv1zk332aiWkBww0Rj1ZD7p4aIMuWhA9tQIM6U/ZM1fuDI1ODC/r77tw8+B64n\n303USrzznlFOX2sz34oYr11PMPvhW7Tj0Yf38+SLs1xeTnnowDYW2zEvzTSpFODBvSMUg4BDUzWu\nNXostGPGqwX2jVfwPM8mmo3ZQkT1Fgv0X8eOHj2qzz777IZ/7sryz5urpK71vb9/7DzPX6yjKA/u\nGeWnHrrn2xqnX1l1NFIObwhQ307G8a2+E/Btf09jzOuXiDynqkfvepwFhTee7yRAGWO2prUGhS09\nfPRGdbchK2OM+XZt6TwFY4wxN7KgYIwxZsCCgjHGmAELCsYYYwYsKBhjjBmwoGCMMWbAgoIxxpiB\ndQ0KIvKIiJwUkdMi8ou3eH2viPyJiDwvIi+IyA+tZ3uMMcbc2boFBRHxgd8AfhA4DPyEiBy+6bB/\nDHxSVR8EPgz85nq1xxhjzN2tZ0/hXcBpVT2rqjHwCeBDNx2jwHD/9xHgyjq2xxhjzF2sZ5mLXcDF\nVY8vAe++6Zh/CvyxiPw9oAp8YB3bY4wx5i7Ws6fw6q2P4ebqez8B/DtV3Q38EPBxEXlVm0TkURF5\nVkSenZubW4emGmOMgfUNCpeAPase7+bVw0M/DXwSQFWPASVg4uYTqepjqnpUVY9OTk6uU3ONMcas\nZ1B4BrhPRPaLSAE3kfz4TcdcAN4PICIP4IKCdQWMMWaTrFtQUNUU+AjwFHACt8roJRH5qIj8SP+w\nnwd+RkS+DvwH4L/XN9oGD8YY8yayrvspqOoTwBM3PffLq34/Drx3PdtgjDFm7Syj2RhjzIAFBWOM\nMQMWFIwxxgxYUDDGGDNgQcEYY8yABQVjjDEDFhSMMcYMWFAwxhgzYEHBGGPMgAUFY4wxAxYUjDHG\nDFhQMMYYM7CmoCAiHxaRX+r/vkdE3rm+zTLGGLMZ7hoUROTXge8HfrL/VBv41+vZKGOMMZtjLaWz\nv1dV3yEizwOo6mJ/0xxjjDFvMmsZPkr6+yYrgIiMA/m6tsoYY8ymWEtQ+A3g/wUmReSfAV8E/sW6\ntsoYY8ymuOvwkar+nog8B3wAEOCvqeqL694yY4wxG+6uQUFEdgJLwB+sfk5Vr6xnw4wxxmy8tUw0\nf47+fAJQBvYAZ4D716tRxhhjNsdaho8eWP1YRN4F/M11a5ExxphN8y1nNKvqnwPvWoe2GGOM2WRr\nmVP4+6seesA7gcV1a5ExxphNs5aewuSqnxHgs8CH1nJyEXlERE6KyGkR+cXbHPNjInJcRF4Skf9n\nrQ03xhjz2lvLnMI/+XZOLCLCV6HHAAAgAElEQVQ+Lsfhg8Al4BkReVxVj6865j7gfwbeq6pLIrL9\n2/ksY4wxr43bBgUR+RTXVx29iqr+1buc+13AaVU92z/fJ3A9jOOrjvkZ4DdUdal/zmtrbLcxxph1\ncKeewq9/h+feBVxc9fgS8O6bjjkEICJ/BvjAP1XVJ7/DzzXGGPNtum1QUNXPfYfnllud9haffx/w\nPmA38KcickRVl284kcijwKMAe/fu/Q6bZYwx5nbWUjr7XhH5hIi8ICKnVn7WcO5LuES3FbuBm7Og\nLwH/WVUTVT0HnMQFiRuo6mOqelRVj05OTq7ho40xxnw71rL66N8B/xZ35/+DwCeBT6zhfc8A94nI\n/n6p7Q8Dj990zP+H26sBEZnADSedXVPLjTHGvObWEhQqqvoUgKqeUdV/TP9CfieqmgIfAZ4CTgCf\nVNWXROSjIvIj/cOeAhZE5DjwJ8D/pKoL384XMcYY851bS+2jSEQEOCMifxu4DKxp6aiqPgE8cdNz\nv7zqdwV+rv9jjDFmk60lKPwsUAP+PvDPgWHgf1jPRhljjNkcd8pT+O+AJ1T1K/2nmsBPbUirjDHG\nbIo7zSn8NHBRRH5HRD7Y35LTGGPMm9htL/Sq+ldweyb8GfAPcQHi10TkezeqccYYYzbWHe/+VXVZ\nVX9bVT8IPAh8E/jXInJuQ1pnjDFmQ61pSEhERoAfxtUuGgc+vZ6NMsYYsznuNNFcwQWBn8DVLPo0\n8DHgs6qab0zzjDHGbKQ7LUm9gNuf+d8CP6qq8cY0yRhjzGa5U1DYp6qtDWuJMcaYTXen1UcWEIwx\nZoux3ANjjDEDaymd/aod1m71nDHGmDe+tfQU/vEtnvul17ohxhhjNt+dlqT+APAIsEtE/tWql4YB\nW5JqjDFvQndafXQNeBHoAS+ter4J/OJ6NsoYY8zmuNMezc8Dz4vIv8f1DPaq6ukNa5kxxpgNt5Y5\nhfcD3wA+AyAibxeRT61rq4wxxmyKtQSFj+LKXCwDqOrXgIPr2ShjjDGbYy1BIVHV5Zue0/VojDHG\nmM21lu04T4jIjwGeiOwH/kfgy+vbLGOMMZthLT2FjwDvxE02fwqIgH+wno0yxhizOe7aU1DVNvCP\n+j/GGGPexO4aFPorjW6eQ6gDzwK/ZSW1jTHmzWMtw0cXgRT4eP8nBhaBtwG/tX5NM8YYs9HWEhS+\nW1V/TFU/paqfwu3E9j2q+reA77nTG0XkERE5KSKnReS2WdAi8qMioiJy9FtrvjHGmNfSWoLClIjs\nXvV4JzDZ/z263ZtExAd+A/hB4DDwEyJy+BbHDQF/H/jKWhttjDFmfawlKPxD4JiIfEZEPgscA/6R\niFSBf3+H970LOK2qZ/vzDp/A7fl8s/8N+BVcjSVjjDGb6I4TzSLiAbPAIdzdvgAvqWq3f8jH7vD2\nXbj5iBWXcJnRq8//ILBHVf+LiPzCHdrxKPAowN69e+/UZGOMMd+BO/YUVDUH/k9V7arqc6r67KqA\ncDdyq1MOXnQB51eBn7/biVT1MVU9qqpHJycn73a4McaYb9Naho8+IyK3Gva5m0vAnlWPdwNXVj0e\nAo4AXxCRV4D3AI/bZLMxxmyetZS5+AgwIiIR0MX1AFRVt93lfc8A9/VLY1wGPgz89ZUXVbUOTKw8\nFpEvAL+gqs9+S9/AGGPMa2YtQWHi7oe8mqqmIvIR4CnAB35HVV8SkY8Cz6rq49/OeY0xxqyftZS5\nyERkBLgXKK166UtreO8TwBM3PffLtzn2fXc7nzHGmPW1ljIXPw38HG410TdwCWtfBt63ri0zxhiz\n4dYy0fwPgKPAK6r6fbiKqTPr2ipjjDGbYi1BobeyDFVECqr6EvCW9W2WMcaYzXDb4SMRCVQ1BWZE\nZBT4I+ApEVnEJbQZY4x5k7nTnMKfA+9Q1R/pP/4nIvJ+YAT49Lq3zBhjzIa7U1B4VUayqn5uHdti\njDFmk90pKEyKyM/d7kVV/Vfr0B5jjDGb6E5BwQdq3LqGkTHGmDehOwWFGVX96Ia1xBhjzKa705JU\n6yEYY8wWc6eg8P4Na4UxxpjXhdsGBVVd3MiGGGOM2XxryWg2xhizRVhQMMYYM2BBwRhjzIAFBWOM\nMQMWFIwxxgxYUDDGGDNgQcEYY8yABQVjjDEDFhSMMcYMWFAwxhgzYEHBGGPMwLoGBRF5REROishp\nEfnFW7z+cyJyXEReEJHPicg969keY4wxd7ZuQUFEfOA3gB8EDgM/ISKHbzrseeCoqr4N+E/Ar6xX\ne4wxxtzdevYU3gWcVtWzqhoDnwA+tPoAVf0TVe30H34Z2L2O7THGGHMX6xkUdgEXVz2+1H/udn4a\n+K/r2B5jjDF3caftOL9Tt9q5TW95oMhPAkeBv3ib1x8FHgXYu3fva9U+Y4wxN1nPnsIlYM+qx7uB\nKzcfJCIfAH4J+BFVjW51IlV9TFWPqurRycnJdWmsMcaY9Q0KzwD3ich+ESkAHwYeX32AiDwI/Btc\nQLi2jm0xxhizBusWFFQ1BT4CPAWcAD6pqi+JyEdF5Ef6h/1LoAb8gYh8TUQev83pjDHGbID1nFNA\nVZ8AnrjpuV9e9fsH1vPzjTHGfGsso9kYY8yABQVjjDEDFhSMMcYMWFAwxhgzYEHBGGPMgAUFY4wx\nAxYUjDHGDFhQMMYYM7CuyWvGGLNWJ2bqPPniLJeXu+waLfPIkSkemB7Z7GatyRu57TezoGCM2XSf\nfuEyH3vqFMvdBE+gWgh4/GuXOThV4/D0CIemqpyabb/qovt6uBh/+oXL/Nrnz5BkOePVAkma8djT\nHR59eP8bMjBYUDDGbIqVC/pLV+o8+8oiSZZTLQakac7Veo8wEKoFn3Lg84dfvcQ79o6yd7xKvZvw\n2NPn+MADk3z2xBwj5ZDpkdLg+Ucf3g/wmgaL2wWfEzN1fu1zZ0BgvFogSnNOzra4f6rGky/OWlAw\nxpi1ODFT57Gnz5FlOcevNGj0UlAoBEovzclUyRLlzHwb8YRqMeBqI2LfRI2RcgjA7x67wOHp4cHj\nlf/+/rHzdJKckXJI4MEXTl7jU89f5vsOjvOTD93zLV+oV9p6q+Dz5IuzpLmyrRoiIpRCn06c8swr\nS3ztUh3gtr2aQ1NVvnR6gecv1lGUB/eM8t6D47fsEW0kUb3lvjevW0ePHtVnn312s5thjPkO/Opn\nTnFursWpay1mGz0a3WTwmnJ9hy5PBM8TSoEgIuweq5CpMlQMuLjU5UffuRtPru/nlavyuRPXeNf+\nbcRpxlcvLFMMPFSVXpLjecLusTJv3Tlyxwvu6gv4hcUOO4aK7J+sDV6vdxNGyiGXl7ucuFJnvhWT\nqSIocaaowlt2DHF45wj1bsIHHpjkPz13mcV2TJzm5KrMNXuUw4DxWgEBFloxiSrv2b+NveNVmr2U\nejd5zYahROQ5VT16t+Ns9ZExZsN9+cw8nz95jbNzLdq9dBAEMoWV+9RcwfMET6Cb5HSTnMtLXTyB\nRi8lTnPOz7dvOG+zl6IoQ6WAFy7VWWxHXF7uMlPvcXm5C0Cjmwzu9k/M1F/VtpWeQb2bMD1SYqEV\ncWq2xVyzNzhmqBRweblLwRfq3ZQozfGAdpzRidz3uW/K9WpGyiG/+YWzXFjoDN673IlpRxndOKVc\nCCgVApJcyTLlaiPCExm898kXZ1/rf/47sqBgjNlQn37hMieuNunGGXmuxLmSqgsI4HoKirs4CUqS\n5cSZUvCE0Beu1nvMNSN8T/mzMwu8Mt8iV6Xev9g/uGeUFy4u8fK1FvVOQi/JqHcT0lwJPGhF2R0v\nuE++ODt43RNholYEgdNz1wNQs5eya7SMAIXAY/tQkcD3iJOcTF1Ae/lam7lmj6FSwKWlDrWiTyn0\nERF6aU6SK/VeyqWlDu0oJVNFVWn0rveaVoLPRrKgYIzZUL977AK1oo/iAsHqzdwF8AQmKgGeJ4BQ\nCDx8IFWlm2S0opTQh3aUsdyJ+ePjs3zh5DVGyiGPPryf9x4c5/kLrgfge0KSuqCS5Tnn5tt4/Q+8\n3QX38nKXodL16daD26uoKout+Ibg88iRKaJMefeBMQqBRztOyYHAEzxRosQNX52fbxP63mCD+nbk\nejn0e0VpljNT79GJ3HDR2bk2f/DcRV6ebQyCz0ayiWZjzIaabfRQhaFiQKOX3jCHMFIO3AqkTNlW\n9cjctZNaEbIcuklKKfBZbCeIQDn0CHyf8wsdDk1VeWB6xN3pVwK6cUa9m5Kr4uEuwFGac2Gxw3/+\n2iVGygWO7BwG3JDRr332Zf78/BLNXkIx8Nk+VCQMPIZLboK5k7iLd8EXKqHHb3/xFS4sdigHQpor\npcAn8TM6qRJnGS9cquMBM8tdvmv3MFeWI0SExXZMMfBIshxPBAWiJKWT5PgC1YJHL854+tQ8h3cO\n888+9NYN/ftYUDDGbKip4RLfnGlQKwZEaU6WuyEX34Nt1QLvPrCNJ74xy1g5YKmbEngQJbkbcsmU\n3M8RETwRygUfVWj0Mn7pUy/xu8cucGGhjSfCWLUAAt04I82VOFV8gdAXunGGLylX6j0+/cJlfvdL\n5zk+08AXIcuURprS6KWUAqgVCwS+8E/+8gMcmKwNViJtqwUkacaffHOObdWQdpTQTa8v3FEgAzpx\nymIrppdkLHViOnFKJfTZPlSiUvBZ7iZ0k5zQF+7ZVqab5ERpTjH0acfZhq8+sqBgjNlQ73/LBF+7\nsEQ3TgEQgUCE6ZESlULA8StNBKXRS+klCYHnEfoe5dBHNSVOoVJwAQGgGWUISquXMNfsUe8mqObM\nt4TAE0YrIXGqNDWh1h8WyhTefWAbhcDnX3/hLKeuNUjS6/MZK6IUqkXFF48vnV7g1Gx7MN8AuCWy\nlSXizC2lXd3roX+uJIcTV1uEPpRD1+YsV96+Z4T7plxP5Xe+eJahUsB4rTR4b57nXGvF6/EnuCML\nCsaYDXNips43r7b5rp1DHL/aIk5zVGG86i6yy50YEEqh54aIEAq+hyKMVULevmeUr5xbJPB9Qt+n\n3o0BBXGT0I1uSsH3iDMo+kInzmh0E4phwEStwK6xyuAufHKoxLVml5evNYnTG4PBCk+gFPqMVws8\nf7HO4Z3K9EjphmOmR8pcWOyQr5oov5kCaQYUhG2VkLlmzGePX+Mr5xYZrxbxPI+C79GOUpY6MVH/\n32XHTZ+1ESwoGGM2zMrKnr9waIr7p0c4PdfmylKXHMX3hNFKgSxXfK9AL8mJs5x2nBL6HksdmBzK\n2DVa4lozphWl5AqlwKMd51SKHoEnFAMfiYVywXPLPNXNPWSqzLUiioHPzpESx84u8PJskyxXhOv5\nEasv6oKbh3DPK7tGy4McBYD5Vo+Li21mG3e/o/c96EYprV5/gl2VJFOuNSPGKwHzrYgr9d4g70JQ\nqoUqJ2bqGzqEZEHBGLNhLi93B3fak0MlJodK5KrM1F0OwPRIic+emKUS+FSKARKlZJlSLQZkuRtS\nCnyfv/v9B/jcN+c5ebVBMfCYHCqx0I7xPSHLcwqB0O7nMngiLo9AXILYrpECf/7KElGS0YkzEMj7\n7XvVXb5CnuW0oox3H9jGoanqoM5RKfCodxMWOwkFD+L85jdf51ZVCVF/3a3fH2MKfY9a0We56yaa\nVSFHKYQeY+UCO4ZLG14uw4KCMWbD7Botc26uxdVmRKuXUisFN2QL17sJw6WQXpKxrVLgVCMaLAP1\nPSFKMt62e4ROrHzybz00SDTL85w/fXmeTpyhKHGSEWVKIBD4QpIpY5WQ3aMBx6+28AXS3E06J7k7\nLr3FuE+Ou6vfO17hvQfH+eyJOQ5tr3G10ePlay1UQXPF9z2KXk4vvfX3DsTNI6xW8AVVZabedbkN\nuevReJ5QDn06Sc6z55foptlr/Fe4s3XNUxCRR0TkpIicFpFfvMXrRRH5j/3XvyIi+9azPcaYzXVo\nqsrzF5dpdBOqBY9GN+H5i8scmqryyJEp6t2EHcNFeknWX/evSH9MJ/Q8FtsxL1xa5jPHZwfDKo8+\nvJ99EzUO7RjC94Q8V8QTfAHP86gWA4qBRydOmWnEBJ7HcH+yuFzwyfV6QPBxd/UrP74HmSo/+s5d\ng0nm/ZM1Hrp3gumRMnu3lVGEJMtJbnHtHir6jJQClH6Gtlz/qZVCl7OQMVh620lcr2S+v1pprhXx\n1fPLfPqFyxv0F1rHnoKI+MBvAB8ELgHPiMjjqnp81WE/DSyp6kER+TDwL4AfX682GWM216nZNu/Y\nO8rVRkSj58bm75+qDVb2NHsJjV7KWLXAhcUOxcDdtwoQZznFwKPeTenEOX/r41/lLxwc56ceuoef\n/eAhwE1k/9wnv86V5e5gFVC9mwzu0gPfTUjPt1J8kf6chNBL3bxChrurHy650hNxmpPmypdOLxBl\nN04y10oBUZwSBh7dOHvV0JOAW0KrWX8iHFQVQfB9Ic3ywXDSzRToJTmh79rya58/w4HJ2oYMI63n\n8NG7gNOqehZARD4BfAhYHRQ+BPzT/u//Cfh1ERF9o1XpM8asyeXlLnvHq+ybuF5c7lqzy5+eXuAv\nvWU7D0wPDwrBocqMJ9R7KXGaoap0opQMODBRpRL6vHSlwceeOsXUcJE4cxPBD+4ZpeB7XGt0mW3E\niLgLdKqQpdq/UAO4QFDwhXLoSlVcXOwSBh6lgk+WuyWmk7WQ5y/W+eDhqRsmmQ9OVvnK2UWGigFJ\nv2zFitBjsBpp33iVa82YWsEnCDxQZamT0I6vdy08Xr0cFty+EpNDRRba8YbNLazn8NEu4OKqx5f6\nz93yGFVNgTowvo5tMsZsol2jZZo3Dbwfv9JkrHK91tBKHsCFpS7lQsDu0TKqICL9MhKwrVqkGPo0\newnn5tu8dKUxKGs924gIfWGx4xLfVgLCilzdMBG4i3CUKSPlgHIhoFzwUIU4UwLfG+ROKDoY3qp3\nE3JVCoHP3vEK79w7CkApFEbLbqgqVxB1vZvzi66IX7noUy0GbB8pM9lPXBsp+Qhu7uLmgFDwBd/3\niFK3ec9G1UBaz6Agt3juVj2sux2DiDwqIs+KyLNzc3OvSeOMMRvv5gtrvZuw1El4YHrohuOGSoGr\nlqquftFYpUC1EOCLUArdAEeUuszfWtEnyXQQUPZsq3D/1BCBB77nEYY+peDGS93NC4WW2glpljFe\nLVIKfXaNltk1Wsb3hFaU8eCeUR6YHuEDD0xyfKbB41+/wvGZBj/6zl385k8d5QMPbKcUBogItaI3\nGIoq+IKQU+8mvHzNBa+FZo+D2yvkCttqxcFKpNXcU4rfXzk1PVLasBpI6zl8dAnYs+rxbuDKbY65\nJCIBMAIs3nwiVX0MeAzcfgrr0lpjzLpbmRhe2avgar3D1eUO//GZDr4nTI8U+b77JikEPnu2Vdgx\nVORqM6IYuDvmUuhT9D16SUaUutIQAoNMZXABZaae8tZdozS6CYEnvHytdUM7br6IqCrzrZhS6LNz\npAi4SqiFwGOsGiLAz/zeM1xc6HJoqsa9kxWOX2nyL548xZ+dXuAvf/c0vTQf7JfQS1xF1W3VApeX\neoMgJMCFpS4XlzqUAp+FduwK/62aW1jJlUhymKwVuHd7Dc/zeOTI1Gv5p7it9QwKzwD3ich+4DLw\nYeCv33TM48DfAI4BPwp83uYTjHlze2B6hAemR/g3/+1l/ujrlwbXwzRXLi71+MPnL3Nk5zB/8737\n+MOvXiFKMoqhxzY/pB1lxJnbrrMcenSSjDSDh3ddH2tfqSz6/fdP8L//15M0ewlZfockAvo5BnHG\n2/eMsmu0zMRQabBfwulrLV680uDSUocsVy4vu/8OlUKGywEvXWnQTXLec2CMz31zvr/PtJCrcmW5\nd0OvxBOXtBbnUC0IO0fLnJlr44vbmEeBUuiS8BSYHiuzb6K2oTuwrVtQUNVURD4CPIUbwvsdVX1J\nRD4KPKuqjwO/DXxcRE7jeggfXq/2GGNeX3732AXAI/Tdcs5cr6+6WejX/Mn794iCUCn4jFUKzDV6\nzDR6zLWuJ4JdWeowXivS7KWcX2izc8Rd1O8ZL/PlM24s3pPrk7+rBZ7LEQj7ZTGiTAermX7pD19g\nvhUzVHLJc90kI0mVQuAGeBZaMVlFybKcTz0/w3sOjHPvZIX/+o1Z8uz6iqTBMtd+opyHe1ArhYzX\nCiy23fcdqxbYM1ah11/fenh6ZNCWjbKuyWuq+gTwxE3P/fKq33vAX1vPNhhjXl9Wtrq81ohQ1UEw\n8MRd4LPc7bi2sgfz23aPMtfs8Y3LdZ57ZYkMBquGRNyyz2fOLxP0y117IoSBz7ZawAsXl/F9j4Lv\n6ik1einRTVlqaX79or3Qjnno3onBa89frA82x0lz7ZegUNLcLW/NcrdhztVGjyRz+0J/+WyDyaEC\nc614UCID3AeMVULq3ZQgcBnOvSRjtBxyrREBylg5HAyNvX3PyIZvsAOW0WyM2UArGcgj5ZDQg+7q\nhUj9JDJfYLxaYLbR4937tzHX7HHszAJLnYTs+qGkuVIMPQr9bOG37nTDK4XAZ6QcMt/qcbXRo9Sf\njygGQin0yfJ0EAhW6h354lYc5bneMHavuLwCcJvnZLlLplNV0swtWS36rnjfeLUAQOP/b+/Mg+S6\nqjv8nbf0Nt0zI81Y0mjxaAFhyULeJIMKQrAh4ALCZgfblClcRUiFSpkC4gKqIECgqJCQigsK8odC\nUWCSGAey4LDYLJZL4LKNRWxLXgrZRjKSF1kzI83WPb28d/LHffPUM9paWD3Tks5X1aX3um+/99Nr\n6Z737r3nd6bqLChkyPgev48iKnV1NR2SojqqUMoHbF65gKHJOvVIKWV9EEERsqHPhUu707/HXGNB\nwTCMOaO51GV/Mcu+w0fqHjePvR8Ym2KyFrF990GiWCnXGmQDb6ZxnUIj0jTr+KePv0C5FhEkNZzH\nphrEcUwu9MiFPpnQI6ophUxAueqK+6T1oHGuqhcsKc0Yu79kRS8P/G4ExNlwl+MjTzYHx53X0niy\nkurAmJ/UaXArhgLfY93SXvoKIb/eO8JE1SWxXb5yAblMwKLuPGsWlRifarBvxHlADfZ1UcoFaa7G\ntZuXt/03mY0FBcMw5oxmQ7xiPmQ5sL8pMEznDwxP1ti4rJsXxmocHK8iaDr5CkcSveqREsdurH54\nokq52mCyFhN4bmjJE2GiGlPKCct7i0zVIw5XGiwqZXhmuEyEa+PmK0Ias9a5vG/LILsPjLNnaNJV\ncYsVTXTGkCasZQNBFfYOu1rMjcQBtTcXJH5NvXz8qlekAWd6CO3ZwxWW9ebZfOlS7n1qmAf2DCMI\nl6xwq7TmusAOWFAwDGMOabae7s6FZHyPcrVBuR7heR7VekToO7fUhgpb1izkJ7te4FD5SNnO5m57\nus5z6EFvPsN4xZXpnB7myQQegUK9ETNedbUWNiwt8cCeQ3RlQwoZnyjWdL5gtHK0o11PPoPvuc5+\nqh5Ri9yxA6bnP9wTiydK3hcmaxGewHmlLH5SEHraDnua6RVYMHNI7Y3rFh/J6J4n2mqIZxiG0Uxz\n8trq8woMjVcZq0bkMz7FjI8nkA0DMr7HRJL5XMoFeElPdazs18ATBhd2saArQ4yQ8V1HPd22K+uR\nCX1etaqP1ecV6S1kyIdearPte9CI3GTxvpEyt/xsN088Pwq44a4VCwv0FbOsXVyimAvTLOl67J4W\nGrELTFP1mIlaRCOK6C/meMsrl3LZ4AJyoc/e4Uk+e8fj6XGfeH6UW362m5u/9wifveNxomSSenii\nyuPPj7Fr/+iM9nOJBQXDMOaM6eS1nnxIPXLJXYWMT6Xm7uRD380bDE3UKOYCnnpxEs9z9Zhnd1bd\nOZ9i1icbehSS0pyeQD1ycwWeuCeTwPMJfY+efMhfvG4VtUhZ2punkPEYrzZ4frTK2FSDWj2mrxAy\nWqmzdfsennh+lGcPVyjlArpzYbqSqBHNyDVLUdxkdaWuZANhaGKK3zxzOLEBDxmZqLF1+x5+tPNZ\ntm7fw2ilzkBPjucOlbn36WG+/5t93PXYAQ5NVllQCBieqKY65hIbPjIMY05pHjr54K0PMjZVd2U0\nA1f3YKxSpxYqq/sLPLj3EGOVBqVswPhUHU9BEnvsRqwUwgARmKhGVOoxoprmImQ8ODBWpSvr8zdv\nW8dbNzrrtWW9eYbGKoxM1tOJ6jixrh4u16hHET35kDsfPcCy3jx7hyYYnqjy+xGXtBbDsWtuJigw\nUW3w1IuTRHHM0ESdcs09DUVRnC617cmHHByfolKPiWLlcLlGPgwYmXRDR/3FbKrDiuwYhnFOMFpp\nkM8ElHIhI+UakcZ0ZQMygUcjhr5ilmrdddJjlbqbYE56/UakFEsBpazPeLXBsyNVQMgHbmlrGLgn\niEtW9KYBAdwQ1l2PvuAmrlWoNtwcQS70GKs0uOuxA6zu78LzhIX5kLt3HySO3d3/RFWPmteYTSBw\nOLHrrtQjJFnUGnrCvU8PM1apsX+kTC70mGo4e+xyLWKqHiNE+J4wMlnn8lULKeWCOc9VsKBgGMa8\n0Z0LGCu7qmrLe/PO5K4es3xhnn/8s4t44vlRPnr7I0QKvYWAw+WGq28sziivrxAwWVcuWt7L+NRQ\nUt/ZY92SIrUYxit19o6UZ9Q5XjfQw4q+PAcnpgj9AM+L8HAriVTda/+hcuqFpHGMINQiFzhC36MR\nx8SxMpUkwnkk8xiKK+BTcMNN9Ugp5nwKoc+hcp1qPSJmOghEVBsRtUacBplyPcIXWNydo7/oXF/n\nyghvGptTMAxj3rhwaQ9rFxfJhj4T1Yhs6LN2cTFNRFs30MNNV65J3FJdqcpixqc3H7KkO8eTB8ss\n6c6ysr/IyxaVGOzrYmFXyBMvTCQrmYSM7x01Nr9+oIflCwosW5BnZV8X9ThJMBPXsQ9N1Mj4HrWG\nyy3wPKEr9CjlAkJf8CV5JcdT3BBULvQoZAK2rO7jwqXdDPTkOK+YdbWgcQl3ucBNckuSz9CInf1G\nbz4g9F2XXG3E6YT8XIUCmk8AAAqDSURBVBnhTWNBwTCMeeOqDYvxfY/1A928Yd0i1g904/szHUHf\nunEZt1x3EYP9RRZ3ZykV3J34ou4cPfkw7XBftqgr7UzjZIipFikblnWnY/PN5+1PvJI8cSuYUGev\nEfhCNvDozjsr7CBZ+lSLY2J1Y/35jM+inhyD/QVyAWn7Zb0FXr64yPu2DLJ+oIcLlpTIhT6TSfJd\nJnClQJf25sgGHlGSWR36Qj7j05Xx8TyhXGukE+Nznatgw0eGYcwbs620l/XmuXbz8qM6wnUDPZy/\nsMCrVi2cseb/vqeHGE7M5PqLOS4b7OXHu17A8yAX+mxY1k1/0WULN4/Nrxvo4eY3r+Vf73uGh/aN\nkg19BnrybF61gId+P8rhcpVqQynlAqqNmKmaCwiFjEuYe+WyXm5+81rWDfQclYjW7Gi6dXuZdQPd\nqGriuxRTyoYUMgFeSThUrpHxXVnQWqTkMz59XSFhEMy5Ed40FhQMw5hXmlcjnYjmxLdplnTnGEuS\nvdzQjs/iUo5XLCnOKPk5bac9+7xffPdG4EgCWei7Za6Vus9EtUZfV45MIOwbqVBpRHRlArasXsgN\nWwZnzFEcS39zwOsphIxVGmxYWuLAWI3RSh1VZVFSanOgJ8eCQoZqI2Z8qsHlK+Y+k3kaCwqGYZwR\nXLVhMVu37wFI/YF83+OmK9ew+8Bkeqd+0xvW8PMnDqaBohUfoeYOvDsfMjbV4NLzeynXItdp9+a5\n6co1M1YxtcLszOU7Hz3AY8+NMjbVoCcfsKiY5ckXJ6g2Ysam6mQDn1X9XdywZfAPv1AvETnTatps\n2rRJd+zYMd8yDMOYB040VPOHtHup5zkdzNW5ROQ3qrrppO0sKBiGYZz9tBoUbPWRYRiGkWJBwTAM\nw0ixoGAYhmGkWFAwDMMwUiwoGIZhGCkWFAzDMIwUCwqGYRhGyhmXpyAiB4FnTsOh+oGh03Cc00kn\naoLO1GWaWqcTdZmm1jldugZV9byTNTrjgsLpQkR2tJLIMZd0oiboTF2mqXU6UZdpap251mXDR4Zh\nGEaKBQXDMAwj5VwOClvnW8Ax6ERN0Jm6TFPrdKIu09Q6c6rrnJ1TMAzDMI7mXH5SMAzDMGZx1gcF\nEblKRH4rIk+JyCeP8fnrROT/RKQhItd0iKaPicjjIrJTRH4hIm2vuNGCpr8UkV0i8rCI/EpE1rdb\nUyu6mtpdIyIqIm1fpdHCtbpRRA4m1+phEfnz+daUtHlP8u/qMRH593ZrakWXiNzSdJ12i8jhDtB0\nvohsE5GHkv+Db+kATYNJX7BTRO4RkeNXDHqpqOpZ+wJ84GlgNZABHgHWz2qzEtgI3Apc0yGargAK\nyfaHgNs7QFN30/bbgTs74Vol7UrAduB+YNN8awJuBL7W7utzippeDjwELEj2F3WCrlntbwK+Od+a\ncGP4H0q21wN7O0DT94D3J9tXAt9pl56z/UnhcuApVf2dqtaA7wLvaG6gqntVdScQd5CmbapaTnbv\nB9p3V9C6prGm3S5gLiajTqor4QvAPwBTHaRpLmlF0weBr6vqIQBVfbFDdDVzPXBbB2hSoDvZ7gGe\n6wBN64FfJNvbjvH5aeNsDwrLgH1N+/uT9+aTU9X0AeAnbVXUoiYR+SsReRrXAX+4zZpa0iUilwAr\nVPWHc6CnJU0JVyeP+t8XkRUdoGktsFZE7hWR+0XkqjZralUX4IZHgFXA3R2g6XPADSKyH/gx7glm\nvjU9AlydbL8LKIlIXzvEnO1BQY7x3nwvt2pZk4jcAGwCvtxWRS1qUtWvq+oa4BPAp9usCU6iS0Q8\n4Bbgr+dAS3raY7w3+1r9L7BSVTcCPwe+3QGaAtwQ0utxd+TfEJHeDtA1zXXA91U1aqMeaE3T9cC3\nVHU58BbgO8m/tfnUdDPwxyLyEPDHwLNAox1izvagsB9ovktbTvsfBU9GS5pE5I3Ap4C3q2q1EzQ1\n8V3gnW1V5DiZrhKwAbhHRPYCrwbuaPNk80mvlaoON/1m/wJc1kY9LWlK2vxAVeuqugf4LS5IzLeu\naa6j/UNH0JqmDwD/AaCq9wE5nP/QvGlS1edU9d2qegmuX0BVR9uipp0TKPP9wt0d/Q73WDo9gXPh\ncdp+i7mZaD6pJuAS3MTTyzvlOjVrAf4U2NEJuma1v4f2TzS3cq0GmrbfBdzfAZquAr6dbPfjhiv6\n5ltX0u4VwF6SvKn51oQbrr0x2V6H66Dbpq1FTf2Al2x/Efh82/S0+0eY7xfu8W930sl+Knnv87g7\ncIDNuEg9CQwDj3WApp8DB4CHk9cdHaDpK8BjiZ5tJ+qc51LXrLZtDwotXqu/S67VI8m1uqADNAnw\nT8DjwC7guk75/XBj+F+aCz0tXqv1wL3J7/cw8KYO0HQN8GTS5htAtl1aLKPZMAzDSDnb5xQMwzCM\nU8CCgmEYhpFiQcEwDMNIsaBgGIZhpFhQMAzDMFIsKBhnNCLyrsQd9YKm91aKyHub9i8+kdOliGwS\nka8m258TkZtPUcNHRKRwCu1vFJHbZr3XnzirZk/wvW/NlZOvce5iQcE407ke+BUuI3aalcB7m/Yv\nxq0DPwoRCVR1h6q+FC+njwAtBwXgv4A/mRVIrsHlo7Q7e90wTogFBeOMRUSKwGtwtgTNQeFLwB8l\nHv2fwCUBXZvsX5s8DWwVkZ8Ct4rI60Wk2VDvIhG5W0SeFJEPJuea0UZEvpbc8X8YWApsE5FtyWdv\nEpH7xNXp+F6iM0Wd4+x2XGb4NKnNg4h8RkQeFJFHE51HeeOIyF4R6U+2N4nIPcl2l4h8M/n+QyIy\n3w6uxhmGBQXjTOaduLoOu4EREbk0ef+TwC9V9WJV/XvgM7iaFBer6u1Jm8uAd6jqe48+LBuBtwJb\ngM+IyNLjCVDVr+JsEK5Q1SuSjvrTwBtV9VJgB/CxY3z1NpJAlhx/LS77GVwths2qugHIA29r6Wo4\nPgXcraqbcXU5viwiXafwfeMcx4KCcSZzPc6cj+TP60/hu3eoauU4n/1AVSuqOoTrqC8/heO+msQm\nQUQeBt4PHKty3g+B14pIN/AeZjqEXiEiD4jILlxBlQtP4fxvAj6ZnPsenJnb+afwfeMcJ5hvAYbx\nh5B4yV8JbBARxVWvUhH5eIuHmDzBZ7O9XxRnU9x8E5U7njTgZ6p6wgClqhURuRNnmHcd8FEAEckB\n/4zzcNonIp87zrma9TR/LsDVqvrbE53fMI6HPSkYZyrXALeq6qCqrlTVFcAe4LXAOM5We5rZ+yfj\nHSKSSwLP64EHgWeA9SKSFZEe4A3HOf79wGtE5GUAIlIQkbXHOc9tuKGlxcn34EgHP5TMRRxvtdFe\njlhyX930/l3ATdPzEEkRIsNoGQsKxpnK9cB/z3rvP3GrjnYCDRF5REQ+ihsCWj890dzCsX8N/AjX\nUX9BnZf9PpzH/k7g33D1jqfZCvxERLap6kFcjebbRGRncowLODY/xU1S366JM6WqHsbVYNgF/A8u\nIB2LvwW+IiK/BJoL03wBCIGdIvJosm8YLWMuqYZhGEaKPSkYhmEYKRYUDMMwjBQLCoZhGEaKBQXD\nMAwjxYKCYRiGkWJBwTAMw0ixoGAYhmGkWFAwDMMwUv4fDxIyNzJTJSwAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f1eeedfc240>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "__author__ = 'mike_bowles'\n",
    "\n",
    "import matplotlib.pyplot as plot\n",
    "from random import uniform\n",
    "\n",
    "#Simulate easy to classify examples\n",
    "\n",
    "x = []\n",
    "target = []\n",
    "for i in range(200):\n",
    "    #make up easy data points\n",
    "    x.append(0.2 + uniform(-0.1, 0.1))\n",
    "    target.append(1.0 + uniform(-0.1, 0.1))\n",
    "    x.append(0.8 + uniform(-0.1, 0.1))\n",
    "    target.append(0.0 + uniform(-0.1, 0.1))\n",
    "\n",
    "\n",
    "plot.scatter(x, target, alpha=0.5)\n",
    "\n",
    "plot.xlabel(\"Attribute Value\")\n",
    "plot.ylabel(\"Target Value\")\n",
    "plot.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### corrCalc.py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Correlation between attribute 2 and 3 \n",
      "0.770938121191\n",
      " \n",
      "Correlation between attribute 2 and 21 \n",
      "0.466548080789\n",
      " \n"
     ]
    }
   ],
   "source": [
    "__author__ = 'mike_bowles'\n",
    "import pandas as pd\n",
    "from pandas import DataFrame\n",
    "from math import sqrt\n",
    "import sys\n",
    "target_url = (\"https://archive.ics.uci.edu/ml/machine-learning-\"\n",
    "\"databases/undocumented/connectionist-bench/sonar/sonar.all-data\")\n",
    "\n",
    "#read rocks versus mines data into pandas data frame\n",
    "rocksVMines = pd.read_csv(target_url,header=None, prefix=\"V\")\n",
    "\n",
    "#calculate correlations between real-valued attributes\n",
    "dataRow2 = rocksVMines.iloc[1,0:60]\n",
    "dataRow3 = rocksVMines.iloc[2,0:60]\n",
    "dataRow21 = rocksVMines.iloc[20,0:60]\n",
    "\n",
    "mean2 = 0.0; mean3 = 0.0; mean21 = 0.0\n",
    "numElt = len(dataRow2)\n",
    "for i in range(numElt):\n",
    "    mean2 += dataRow2[i]/numElt\n",
    "    mean3 += dataRow3[i]/numElt\n",
    "    mean21 += dataRow21[i]/numElt\n",
    "\n",
    "var2 = 0.0; var3 = 0.0; var21 = 0.0\n",
    "for i in range(numElt):\n",
    "    var2 += (dataRow2[i] - mean2) * (dataRow2[i] - mean2)/numElt\n",
    "    var3 += (dataRow3[i] - mean3) * (dataRow3[i] - mean3)/numElt\n",
    "    var21 += (dataRow21[i] - mean21) * (dataRow21[i] - mean21)/numElt\n",
    "\n",
    "corr23 = 0.0; corr221 = 0.0\n",
    "for i in range(numElt):\n",
    "    corr23 += (dataRow2[i] - mean2) * \\\n",
    "              (dataRow3[i] - mean3) / (sqrt(var2*var3) * numElt)\n",
    "    corr221 += (dataRow2[i] - mean2) * \\\n",
    "               (dataRow21[i] - mean21) / (sqrt(var2*var21) * numElt)\n",
    "\n",
    "sys.stdout.write(\"Correlation between attribute 2 and 3 \\n\")\n",
    "print(corr23)\n",
    "sys.stdout.write(\" \\n\")\n",
    "\n",
    "sys.stdout.write(\"Correlation between attribute 2 and 21 \\n\")\n",
    "print(corr221)\n",
    "sys.stdout.write(\" \\n\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### corrPlot.py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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YD9Qvj3wLsEzJRvXHkiS0SyU9BGyh+XakZm3xKqlmZlbjloKZmdU4KZiZWY2T\ngpmZ1TgpmJlZjZOCmZnVOCmYmVmNk4KZmdU4KZiZWc3/B3+tDnaOWfekAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f1ee4aafd68>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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xvguAF0fEUEXF1ZW8UEBxT5KMAJ6lVLI7rVOSKqDTKHVJ/XNy/P9JOj45/l8r\nzi+/f9IKelTS+UmckvRbLfxss5qcFKwoFgH/HTg9GYh9QM03cv8ocKikh4D/Bdxf45xlwO1Vx77I\nC11I1wMPSboxqUh6j6SHJa1OEfN3KA1OPww8WvFzVgB3AuuByvLINwHLVdqo/hhKCe0iSQ8Cm6m9\nHalZS1wl1czMytxSMDOzMicFMzMrc1IwM7MyJwUzMytzUjAzszInBTMzK3NSMDOzMicFMzMr+/+M\nzPSnjy5Z6gAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f1ee43f47f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "__author__ = 'mike_bowles'\n",
    "import pandas as pd\n",
    "from pandas import DataFrame\n",
    "import matplotlib.pyplot as plot\n",
    "target_url = (\"https://archive.ics.uci.edu/ml/machine-learning-\"\n",
    "\"databases/undocumented/connectionist-bench/sonar/sonar.all-data\")\n",
    "\n",
    "#read rocks versus mines data into pandas data frame\n",
    "rocksVMines = pd.read_csv(target_url,header=None, prefix=\"V\")\n",
    "\n",
    "#calculate correlations between real-valued attributes\n",
    "dataRow2 = rocksVMines.iloc[1,0:60]\n",
    "dataRow3 = rocksVMines.iloc[2,0:60]\n",
    "\n",
    "plot.scatter(dataRow2, dataRow3)\n",
    "\n",
    "\n",
    "plot.xlabel(\"2nd Attribute\")\n",
    "plot.ylabel((\"3rd Attribute\"))\n",
    "plot.show()\n",
    "\n",
    "dataRow21 = rocksVMines.iloc[20,0:60]\n",
    "\n",
    "plot.scatter(dataRow2, dataRow21)\n",
    "\n",
    "\n",
    "plot.xlabel(\"2nd Attribute\")\n",
    "plot.ylabel((\"21st Attribute\"))\n",
    "plot.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### glassCorrHeatMap.py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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M5xH3VC6Nr6obgF/3nWNLVfVQVd08uP44sJbZJ1SfmaqqnhjcXDS49P7KdZIDgbcBX+k7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\ngg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f1ee6f00c18>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "__author__ = 'mike_bowles'\n",
    "import pandas as pd\n",
    "from pandas import DataFrame\n",
    "from pylab import *\n",
    "import matplotlib.pyplot as plot\n",
    "from math import exp\n",
    "\n",
    "target_url = (\"https://archive.ics.uci.edu/ml/machine-\"\n",
    "              \"learning-databases/glass/glass.data\")\n",
    "glass = pd.read_csv(target_url,header=None, prefix=\"V\")\n",
    "glass.columns = ['Id', 'RI', 'Na', 'Mg', 'Al', 'Si',\n",
    "                 'K', 'Ca', 'Ba', 'Fe', 'Type']\n",
    "ncols = len(glass.columns)\n",
    "\n",
    "#calculate correlation matrix\n",
    "corMat = DataFrame(glass.iloc[:, 1:(ncols - 1)].corr())\n",
    "\n",
    "#visualize correlations using heatmap\n",
    "plot.pcolor(corMat)\n",
    "plot.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### glassParallelPlot.py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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wGpAqOxgK2jfpEzgQD2GgmC1uXAATi9kcP97OlaHklrMa1qLMZRXWKsy8g4is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\nKKYh+SZIFSoh/Pmr4FVR7QO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8l5/72cf4+EePrkxtWpHA6Ijv6jjFRvINnfUhQKPzd1df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\nsxB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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f1ee399c710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "__author__ = 'mike_bowles'\n",
    "import pandas as pd\n",
    "from pandas import DataFrame\n",
    "from pylab import *\n",
    "import matplotlib.pyplot as plot\n",
    "\n",
    "target_url = (\"https://archive.ics.uci.edu/ml/machine-\"\n",
    "              \"learning-databases/glass/glass.data\")\n",
    "glass = pd.read_csv(target_url,header=None, prefix=\"V\")\n",
    "glass.columns = ['Id', 'RI', 'Na', 'Mg', 'Al', 'Si',\n",
    "                 'K', 'Ca', 'Ba', 'Fe', 'Type']\n",
    "\n",
    "\n",
    "glassNormalized = glass\n",
    "ncols = len(glassNormalized.columns)\n",
    "nrows = len(glassNormalized.index)\n",
    "summary = glassNormalized.describe()\n",
    "nDataCol = ncols - 1\n",
    "\n",
    "#normalize except for labels\n",
    "for i in range(ncols - 1):\n",
    "    mean = summary.iloc[1, i]\n",
    "    sd = summary.iloc[2, i]\n",
    "    glassNormalized.iloc[:,i:(i + 1)] = \\\n",
    "        (glassNormalized.iloc[:,i:(i + 1)] - mean) / sd\n",
    "\n",
    "#Plot Parallel Coordinate Graph with normalized values\n",
    "for i in range(nrows):\n",
    "    #plot rows of data as if they were series data\n",
    "    dataRow = glassNormalized.iloc[i,1:nDataCol]\n",
    "    labelColor = glassNormalized.iloc[i,nDataCol]/7.0\n",
    "    dataRow.plot(color=plot.cm.RdYlBu(labelColor), alpha=0.5)\n",
    "\n",
    "plot.xlabel(\"Attribute Index\")\n",
    "plot.ylabel((\"Attribute Values\"))\n",
    "plot.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### glassSummary.py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   Id       RI     Na    Mg    Al     Si     K    Ca   Ba   Fe  Type\n",
      "0   1  1.52101  13.64  4.49  1.10  71.78  0.06  8.75  0.0  0.0     1\n",
      "1   2  1.51761  13.89  3.60  1.36  72.73  0.48  7.83  0.0  0.0     1\n",
      "2   3  1.51618  13.53  3.55  1.54  72.99  0.39  7.78  0.0  0.0     1\n",
      "3   4  1.51766  13.21  3.69  1.29  72.61  0.57  8.22  0.0  0.0     1\n",
      "4   5  1.51742  13.27  3.62  1.24  73.08  0.55  8.07  0.0  0.0     1\n",
      "               Id          RI          Na          Mg          Al          Si  \\\n",
      "count  214.000000  214.000000  214.000000  214.000000  214.000000  214.000000   \n",
      "mean   107.500000    1.518365   13.407850    2.684533    1.444907   72.650935   \n",
      "std     61.920648    0.003037    0.816604    1.442408    0.499270    0.774546   \n",
      "min      1.000000    1.511150   10.730000    0.000000    0.290000   69.810000   \n",
      "25%     54.250000    1.516523   12.907500    2.115000    1.190000   72.280000   \n",
      "50%    107.500000    1.517680   13.300000    3.480000    1.360000   72.790000   \n",
      "75%    160.750000    1.519157   13.825000    3.600000    1.630000   73.087500   \n",
      "max    214.000000    1.533930   17.380000    4.490000    3.500000   75.410000   \n",
      "\n",
      "                K          Ca          Ba          Fe        Type  \n",
      "count  214.000000  214.000000  214.000000  214.000000  214.000000  \n",
      "mean     0.497056    8.956963    0.175047    0.057009    2.780374  \n",
      "std      0.652192    1.423153    0.497219    0.097439    2.103739  \n",
      "min      0.000000    5.430000    0.000000    0.000000    1.000000  \n",
      "25%      0.122500    8.240000    0.000000    0.000000    1.000000  \n",
      "50%      0.555000    8.600000    0.000000    0.000000    2.000000  \n",
      "75%      0.610000    9.172500    0.000000    0.100000    3.000000  \n",
      "max      6.210000   16.190000    3.150000    0.510000    7.000000  \n"
     ]
    },
    {
     "data": {
      "image/png": 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84MtnkXFCGLah4tNnSRtpnR8sIUzs/ZnKRvvmsHwWQceQjW2EIYZsbWM07e3t\nNDc3D3VMSyaTNDY2jv/GSQjLZxGmOwQv/RCeBk4vNhppnQkRLwdYLr/YYZNpgiwtLc1SJGYsjY2N\nOUsAZnyjJgQRmYfTeWyGpE+lORuYOdr7jDld0CdjS47pgv5/mPAa6w7hGuDjOP0DWjiVEN4A7sxt\nWJMXloM9LHEEzcOtbN6ciCGz4yIbx4Qlx1OsSfRbjTWF5iMi8v+ARlV9zMeYJi0sB7udBM1I7LgI\nmRy0lJrqxhz+WlVPAn/qUyzGGGMC5GU+hCdF5NMics5pw1kYYzIwfGKmVFHSSOuM8YuXVkbL3cdP\nDFuXjaErjMlrVjxkUoKuW0rxMtppZdb2ZowxJk2YLgw8zTwhIjXA+UBxap2qPpqroIwxxvhv3IQg\nIncBl+MkhG8DS4AuwBKCMcZMI14qlT+CMznOL1T1JuACwAYpN8aYacZLQnjTbX56QkRm40yWYxXK\nxhgzzXipQ9guImcCD+JMmnMU+GFOozLGGOM7L62M/sz9cb2IfAeYrarP5zYsY4wxfvNSqXzZSOtU\n9anchGSMMSYIXoqM/mLYz8XAxThFR75PkGOMya7ROkSdvj5MbeVN7oxbqayqHxq2XA3UAL/MfWjG\nmFxTVVSVtrY2Kisr6ejooL+/n46ODiorK2lra7NkkEfGnTHtLW9wLh2eV9Xfy01IoxtvxjQvwjCi\nZBhiCEscYYghTHEEpaamhoaGBjZt2jQ0W1nq+e7du4MOz2QoazOmiUgrzthF4NxRXAg8l1l4xpgw\n2bNnD8eOHWPjxo3U1dXR1dXFihUr2Lt3b9ChGR956YewHafOYAfwfWCNqt6Q06jMtNfe3k5NTQ3g\nXJ22t7cHHFF+Kyoqoqmpifr6egoLC6mvr6epqYmioqKgQzM+8pIQvgbscpevq+p/5TYkM921t7eT\nTCZpbW0FoLW1lWQyaUkhQP39/bS2ttLZ2cnAwACdnZ20trbS398fdGjGR6PWIYhIIXAv8MfAXpzk\n8TagVVX/VkTepaq7JrVTkXuBDwH9wE+Bm1T18Hjvm0wdgpdhZf0uOw5LeXUQcYTx/wHh+Z8ExeoQ\npjevdQhj3SG0ALOAClW9SFXfBVQBbxeRLwLfyCC+J4EaVX0n8D/AHRlsa0zDW1FUV1cTiUSorq4e\naj2RLyeB0ydeCWpCFlVFRIhGo7S0tNDb20tLSwvRaDTvT8pBSiaTtLW10draSl9fH62trbS1tZFM\nJoMOzfgpdVI8fQF+gnsHcdr6KHAIuGS0905kAT4MPObltRdddJFORltbm1ZWVmpHR4f29/drR0eH\nVlZWaltb26S2lynnY89fIqK96Y7cAAAPCUlEQVS33HJL2rpbbrlFRcSX/eM0khh3yTdtbW1aXV2t\nkUhEq6urA/t+mOwDtquHc+xYdwgn3Q2dnkAGgYOq+oNsJCScGdk2j/ZLEVkpIttFZPvBgwcntYPm\n5mY2btyYVmG2ceNGmpubJxuzyYCqsnnz5rTy6s2bN/t2d+Dli+FXLMaEyVgJYY+I/MnpK0XkBqB7\nvA2LyH+IyO4RlmuHvSYJnAAeG207qrpBVWtVtba8vHy83Y6ou7uburq6tHV1dXV0d4/7Z5gciMVi\nLFiwgCVLllBUVMSSJUtYsGABsZiNqh6U9vZ2Vq9eTW9vLwC9vb2sXr3aKvrzzRhXRwuAZ4Dv4dQn\n/B2wDWek0wVer7LG2P6NOM1YZ3p9z2SLjKqrq7WjoyNtXUdHh1ZXV09qe5kiD4sjhlu8eLECWlpa\nmva4ePHioEPLW/F4XOfPn59WrDp//nyNx+NBh2ayAI9FRqN2TFPV/cC7ReQKoBoQYLOqbs00CYnI\n+4E1wPtU9Vim2xtPMpnk2muvpa+vj4GBAQoLCykuLuZLX/pSrndtRrBnzx5mzJjB0aNHATh69Cgz\nZsxgz549AUeWv3p6etiyZQv19fUA1NfX88gjj7B48eKAIzN+8jKWUYeqtqrqF7KRDFzrgDOAJ0Xk\nWRFZn6Xtjujpp5+mt7eXsrIyAMrKyujt7eXpp5/O5W7fwjpjOXp6enjiiSfo7+9HVenv7+eJJ56g\np6cn6NCMyW9ebiPCsky2yCgWi2lLS0vaupaWFo3FYpPa3kRhLVrSALply5a0dVu2bMm7zyFM4vG4\nzpkzRysqKjQSiWhFRYXOmTPHioymCbLQymjaOH78OKtWrUpbt2rVKo4fP+7L/lWV6upqOjo60j78\njo4Oqqur865FSzwe58Ybb0xrZXTjjTcSj8d9jyV11xaNRvP6rq2hoYEjR47w5ptvcvLkSd58802O\nHDlCQ0ND0KEZP3nJGmFZpuodgqpqJBLR/v7+tHX9/f0aiUR8iyEs2tratLy8PO1qtLy83Pd272Hr\nnxKk6upqTSaTaf0QUs/N1IfHO4TAT/ITWSabEJqamrSgoEBbWlq0t7dXW1patKCgQJuamia1vcmw\nL1y6MHSCsv/JKXbBMr1ZQjhNU1OTxmIxBTQWi/maDFL7DzopmXQiohUVFWl3CBUVFb71mA6TsDXN\nNtllCSFk7Go0fGKxmC5btiztf7Js2TJfixLDworPpjevCWHCM6YFKRszpgUlGo3S19dHYWHh0LqB\ngQGKi4sZHBwMMLL8JSJEIhHe9ra38dprrw09njx5kqn0vciW9vZ2mpubh0Y7TSaTNDY2Bh2WyYKs\nzZhmsqOqqorrrruOzZs3c/z4cWKxGEuWLKGqqiro0PJWQUEBxcXFFBcXo6oUFxczc+ZM+vr6gg4t\nEI2NjZYA8lxeNDsNgwULFrBp0yaWL1/O4cOHWb58OZs2bWLBggVBh5a3Tpw4QUlJCQ899BDHjx/n\noYceoqSkhBMnTgQdmjGBsITgk23btrFs2TKeeuopysrKeOqpp1i2bBnbtm0LOrS8dtNNN5FIJCgu\nLiaRSHDTTTcFHZIxgbE6BJ+ICL29vcycOXNo3bFjxygpKcnL8uowOOecczhy5AilpaW88sorLFy4\nkEOHDnHGGWewb9++oMMzJmuyMWOayaJYLMb69elDNq1fv96GfA6Q9c41Jp0lBJ/cfPPNrFmzhvvu\nu49jx45x3333sWbNGm6++eagQ8tbnZ2dLF26lMOHnem8Dx8+zNKlS+ns7Aw4MmOCYUVGPrrmmmt4\n8sknnfa+Ilx99dV897vfDTqsvBWJRDj33HN56KGHqKuro6uri+XLl/Pyyy9z8uTJoMMzJmusyChk\n2tvbeemll9i6dSv9/f1s3bqVl156KW8HUwuDoqIiEolE2tSqiUSCoqKioEMzJhCWEHxi8zqHT39/\nP+vWrUsbdXXdunX09/cHHZoxgbAiI59YT+XwqampoaGhgU2bNg31zk093717d9DhGZM1VmQUMlVV\nVXR1daWt6+rqsp7KAUomk2zYsCFtYvkNGzaQTCYDjsyYYFhC8EkymWTFihVpxRMrVqywk09ITKU7\nZWNyxcYy8klqjJhEIjFUPNHc3GxjxwSoubmZlStXsmnTJkSEkpISli1bZv8Xk7esDsHkLWt2avKF\n1SEYMw5rdmpMOksIJm9Zs1Nj0lkdgslb559/Pg0NDWn1Otdffz2bNm0KOjRjAhHoHYKIfFpEVETm\nBhmHyU/JZJK2tjZaW1vp6+ujtbWVtrY2a/ll8lZgdwgicg5wNfBKUDGY/GYtv4xJF1grIxH5OvDX\nwBNArar+arz3WCsjY4yZuFC3MhKRpcB+VX3Ow2tXish2Edl+8OBBH6Izxpj8lLMiIxH5D2DeCL9K\nAncCi71sR1U3ABvAuUPIWoDGGGPS5CwhqOpVI60Xkd8DKoHnRAQgDuwUkYtV9Re5iscYY8zYfK9U\nVtUXgLelnovIXjzWIRhjjMkd65hmjDEGmGJjGYnIQeDlDDczFwj6biQMMUA44ghDDBCOOMIQA4Qj\njjDEAOGIIxsxnKuq5eO9aEolhGwQke1eml9N9xjCEkcYYghLHGGIISxxhCGGsMThZwxWZGSMMQaw\nhGCMMcaVjwlhQ9ABEI4YIBxxhCEGCEccYYgBwhFHGGKAcMThWwx5V4dgjDFmZPl4h2CMMWYEeZMQ\nROQhEXlNRHYHGMM5ItIpIt0i8qKIrA4ghmIR+aGIPOfG8Hm/YxgWS1REdonIvwUYw14ReUFEnhWR\nwEZOFJEzReTrIvLf7vHxHp/3f577GaSWN0Tkk37GMCyWP3ePzd0i0i4ixQHEsNrd/4t+fg4jnadE\npExEnhSRl9zH0lztP28SAvAV4P0Bx3ACuE1Vq4BLgE+IyPk+x3AcuEJVLwAuBN4vIpf4HEPKaqA7\noH0PV6+qFwbcvPB+4Duq+g7gAnz+XFT1x+5ncCFwEXAM+KafMQCIyALgVpzRC2qAKPAxn2OoAW4G\nLsb5X3xQRH7Hp91/hbeep24Htqrq7wBb3ec5kTcJQVWfAl4POIYDqrrT/fkIzpd+gc8xqKoedZ8W\nuovvFUkiEgf+APiy3/sOGxGZDVwGbARQ1X5VPRxgSFcCP1XVTDuBTlYBMENECoCZwKs+778K+IGq\nHlPVE8A24MN+7HiU89S1wCPuz48ADbnaf94khLARkQrgXcAzAew7KiLPAq8BT6qq7zEA/wB8BjgZ\nwL6HU2CLiOwQkZUBxfB24CDwsFuE9mURKQkoFnCuyNuD2LGq7gf+DmfirAPAb1R1i89h7AYuE5Gz\nRGQm8AHgHJ9jGO5sVT0AzkUlw8aCyzZLCAEQkVnA48AnVfUNv/evqoNu0UAcuNi9RfaNiHwQeE1V\nd/i531FcqqqLgCU4RXiXBRBDAbAI+KKqvgvoJYfFAmMRkSJgKfC1gPZfinNFXAn8FlAiIjf4GYOq\ndgP3AE8C3wGewynunfYsIfhMRApxksFjqvqNIGNxiyW+h/91K5cCS92Rbv8JuEJEvupzDACo6qvu\n42s4ZeYXBxBGD9Az7E7t6zgJIghLgJ2q+suA9n8V8HNVPaiqA8A3gPf6HYSqblTVRap6GU4Rzkt+\nxzDML0VkPoD7+FqudmQJwUfiTACxEehW1fsCiqFcRM50f56B8wX8bz9jUNU7VDWuqhU4xRMdqurr\nVSCAiJSIyBmpn3EmbfK9FZo7D8g+ETnPXXUlsMfvOFyNBFRc5HoFuEREZrrflysJoOGBiLzNfVwI\n/CHBfibfAm50f74RZ9rhnPB9PoSgiEg7cDkwV0R6gLtUdaPPYVwK/DHwgluGD3Cnqn7bxxjmA4+I\nSBTnguBfVDWwZp8BOxv4pjtRUwHQpqrfCSiWBPCYW2TzM+AmvwNwy8uvBv7U732nqOoz7nzrO3GK\naXYRTG/hx0XkLGAA+ISqHvJjpyOdp4C/Bf5FRFbgJMw/ytn+raeyMcYYsCIjY4wxLksIxhhjAEsI\nxhhjXJYQjDHGAJYQjDHGuCwhmClLRD4sIioi7xi2rkJErh/2/EIR+cAY26gVkS+4P/+ViHx6gjF8\n0m2uOZH3fEVEPjLB9+wVkbkTeY8xE2UJwUxljUAX6aNhVgDXD3t+Ic5YNG8hIgWqul1Vb80ghk/i\nDMBmzJRnCcFMSe54UJcCK0hPCH8L/C93TP81wP8BPuo+/6h7F7BBRLYAj4rI5afNx3CBiHS4Y8/f\n7O4r7TUisk5EPi4it+KMt9MpIp3u7xaLyPdFZKeIfM2Nc6y/Y6+IfN59/Qupux13YLUt7mB3XwJk\n2HtuEGdOi2dF5EvuYIXnujHPFZGIiPyniCye/Cds8pElBDNVNeDMH/A/wOsikhr753bgP92x/e8B\nPgf8s/v8n93XXARcq6rXv3WzvBNnWO73AJ8Tkd8aLQBV/QLO0Mz1qlrvFul8FrjKHTBvO/ApD3/L\nr9zXfxFIFVndBXS5g919C1gIICJVwEdxBuW7EBgElrlDVd8DrAduA/YEMEqomeLyZugKM+004gyh\nDc4AeY04wx148S1VfXOU3z3h/u5N96r/YsDr3ASXAOcD/+UOh1EEfN/D+1KDHO7AGTcHnPkR/hBA\nVf9dRFJDJ1yJk9B+5O5jBu5gZ6r6ZRH5I2AVTlGZMRNiCcFMOe4YM1cANSKiOLNqqYh8xuMmesf4\n3eljuSjOmDrD76ZHm9JRcOaXaPQYR8px93GQ9O/kSOPKCPCIqt7xll84ldtx9+ks4MgE4zB5zoqM\nzFT0EeBRVT1XVStU9Rzg50AdzknwjGGvPf35eK4VZ97ps3AGGfsR8DJwvojERGQOzlX6SNv/AXCp\niPw2OCdoEfndif95ADwFLHO3swRIzaO7FfjIsNE4y0TkXPd39wCP4RSTPTjJ/Zo8ZgnBTEWNvHW+\n38dxWhc9D5wQkedE5M+BTpyT+bMi8lEP2/4h8O84J/e/VtVXVXUf8C/uth/DGYEzZQOwWUQ6VfUg\n8HGgXUSed7fxDibn8zizdu3EGZb7FQBV3YNTT7HF3ceTwHwReR/w+8A9qvoY0C8ivo+YaqY2G+3U\nGGMMYHcIxhhjXJYQjDHGAJYQjDHGuCwhGGOMASwhGGOMcVlCMMYYA1hCMMYY47KEYIwxBoD/D5o6\n9V/JhYyGAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f1ee52c5a20>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "__author__ = 'mike_bowles'\n",
    "import pandas as pd\n",
    "from pandas import DataFrame\n",
    "from pylab import *\n",
    "import matplotlib.pyplot as plot\n",
    "\n",
    "target_url = (\"https://archive.ics.uci.edu/ml/machine-\"\n",
    "              \"learning-databases/glass/glass.data\")\n",
    "\n",
    "glass = pd.read_csv(target_url,header=None, prefix=\"V\")\n",
    "glass.columns = ['Id', 'RI', 'Na', 'Mg', 'Al', 'Si',\n",
    "                 'K', 'Ca', 'Ba', 'Fe', 'Type']\n",
    "\n",
    "print(glass.head())\n",
    "\n",
    "#generate statistical summaries\n",
    "summary = glass.describe()\n",
    "print(summary)\n",
    "ncol1 = len(glass.columns)\n",
    "\n",
    "glassNormalized = glass.iloc[:, 1:ncol1]\n",
    "ncol2 = len(glassNormalized.columns)\n",
    "summary2 = glassNormalized.describe()\n",
    "\n",
    "for i in range(ncol2):\n",
    "    mean = summary2.iloc[1, i]\n",
    "    sd = summary2.iloc[2, i]\n",
    "    glassNormalized.iloc[:,i:(i + 1)] = \\\n",
    "        (glassNormalized.iloc[:,i:(i + 1)] - mean) / sd\n",
    "\n",
    "array = glassNormalized.values\n",
    "boxplot(array)\n",
    "plot.xlabel(\"Attribute Index\")\n",
    "plot.ylabel((\"Quartile Ranges - Normalized \"))\n",
    "show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### linePlots.py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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ieBeObgKSpJdGwyNLB0UjQZ0IT4k7COguQtfx0NCQJMkDgkX6WXPbNmsZXAxi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\nKE69TKpGobl5+a6ODoFuve8+kSKbz2h8f/EmfIuT3CX/hFS9hG/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rn8SVfNBh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\nBYfD4XBEcErB4XA4HBGcUnA4HA5HhP8HRqyL7OLopL4AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f1ee6ecf470>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "__author__ = 'mike_bowles'\n",
    "import pandas as pd\n",
    "from pandas import DataFrame\n",
    "import matplotlib.pyplot as plot\n",
    "target_url = (\"https://archive.ics.uci.edu/ml/machine-learning-\"\n",
    "\"databases/undocumented/connectionist-bench/sonar/sonar.all-data\")\n",
    "\n",
    "#read rocks versus mines data into pandas data frame\n",
    "rocksVMines = pd.read_csv(target_url,header=None, prefix=\"V\")\n",
    "\n",
    "for i in range(208):\n",
    "    #assign color based on color based on \"M\" or \"R\" labels\n",
    "    if rocksVMines.iat[i,60] == \"M\":\n",
    "        pcolor = \"red\"\n",
    "    else:\n",
    "        pcolor = \"blue\"\n",
    "\n",
    "    #plot rows of data as if they were series data\n",
    "    dataRow = rocksVMines.iloc[i,0:60]\n",
    "    dataRow.plot(color=pcolor, alpha=0.5)\n",
    "\n",
    "plot.xlabel(\"Attribute Index\")\n",
    "plot.ylabel((\"Attribute Values\"))\n",
    "plot.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### logitCurve.py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f1ee4aaf0f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "__author__ = 'mike_bowles'\n",
    "import matplotlib.pyplot as plot\n",
    "from math import exp\n",
    "\n",
    "x = [i*0.1 for i in range(-90, 91)]\n",
    "y = [1.0/(1.0 + exp(-i*0.1)) for i in range(-90, 91)]\n",
    "plot.scatter(x, y)\n",
    "plot.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### pandasReadSummarize.py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "       V0      V1      V2      V3      V4      V5      V6      V7      V8  \\\n",
      "0  0.0200  0.0371  0.0428  0.0207  0.0954  0.0986  0.1539  0.1601  0.3109   \n",
      "1  0.0453  0.0523  0.0843  0.0689  0.1183  0.2583  0.2156  0.3481  0.3337   \n",
      "2  0.0262  0.0582  0.1099  0.1083  0.0974  0.2280  0.2431  0.3771  0.5598   \n",
      "3  0.0100  0.0171  0.0623  0.0205  0.0205  0.0368  0.1098  0.1276  0.0598   \n",
      "4  0.0762  0.0666  0.0481  0.0394  0.0590  0.0649  0.1209  0.2467  0.3564   \n",
      "\n",
      "       V9 ...      V51     V52     V53     V54     V55     V56     V57  \\\n",
      "0  0.2111 ...   0.0027  0.0065  0.0159  0.0072  0.0167  0.0180  0.0084   \n",
      "1  0.2872 ...   0.0084  0.0089  0.0048  0.0094  0.0191  0.0140  0.0049   \n",
      "2  0.6194 ...   0.0232  0.0166  0.0095  0.0180  0.0244  0.0316  0.0164   \n",
      "3  0.1264 ...   0.0121  0.0036  0.0150  0.0085  0.0073  0.0050  0.0044   \n",
      "4  0.4459 ...   0.0031  0.0054  0.0105  0.0110  0.0015  0.0072  0.0048   \n",
      "\n",
      "      V58     V59  V60  \n",
      "0  0.0090  0.0032    R  \n",
      "1  0.0052  0.0044    R  \n",
      "2  0.0095  0.0078    R  \n",
      "3  0.0040  0.0117    R  \n",
      "4  0.0107  0.0094    R  \n",
      "\n",
      "[5 rows x 61 columns]\n",
      "         V0      V1      V2      V3      V4      V5      V6      V7      V8  \\\n",
      "203  0.0187  0.0346  0.0168  0.0177  0.0393  0.1630  0.2028  0.1694  0.2328   \n",
      "204  0.0323  0.0101  0.0298  0.0564  0.0760  0.0958  0.0990  0.1018  0.1030   \n",
      "205  0.0522  0.0437  0.0180  0.0292  0.0351  0.1171  0.1257  0.1178  0.1258   \n",
      "206  0.0303  0.0353  0.0490  0.0608  0.0167  0.1354  0.1465  0.1123  0.1945   \n",
      "207  0.0260  0.0363  0.0136  0.0272  0.0214  0.0338  0.0655  0.1400  0.1843   \n",
      "\n",
      "         V9 ...      V51     V52     V53     V54     V55     V56     V57  \\\n",
      "203  0.2684 ...   0.0116  0.0098  0.0199  0.0033  0.0101  0.0065  0.0115   \n",
      "204  0.2154 ...   0.0061  0.0093  0.0135  0.0063  0.0063  0.0034  0.0032   \n",
      "205  0.2529 ...   0.0160  0.0029  0.0051  0.0062  0.0089  0.0140  0.0138   \n",
      "206  0.2354 ...   0.0086  0.0046  0.0126  0.0036  0.0035  0.0034  0.0079   \n",
      "207  0.2354 ...   0.0146  0.0129  0.0047  0.0039  0.0061  0.0040  0.0036   \n",
      "\n",
      "        V58     V59  V60  \n",
      "203  0.0193  0.0157    M  \n",
      "204  0.0062  0.0067    M  \n",
      "205  0.0077  0.0031    M  \n",
      "206  0.0036  0.0048    M  \n",
      "207  0.0061  0.0115    M  \n",
      "\n",
      "[5 rows x 61 columns]\n",
      "               V0          V1          V2          V3          V4          V5  \\\n",
      "count  208.000000  208.000000  208.000000  208.000000  208.000000  208.000000   \n",
      "mean     0.029164    0.038437    0.043832    0.053892    0.075202    0.104570   \n",
      "std      0.022991    0.032960    0.038428    0.046528    0.055552    0.059105   \n",
      "min      0.001500    0.000600    0.001500    0.005800    0.006700    0.010200   \n",
      "25%      0.013350    0.016450    0.018950    0.024375    0.038050    0.067025   \n",
      "50%      0.022800    0.030800    0.034300    0.044050    0.062500    0.092150   \n",
      "75%      0.035550    0.047950    0.057950    0.064500    0.100275    0.134125   \n",
      "max      0.137100    0.233900    0.305900    0.426400    0.401000    0.382300   \n",
      "\n",
      "               V6          V7          V8          V9     ...             V50  \\\n",
      "count  208.000000  208.000000  208.000000  208.000000     ...      208.000000   \n",
      "mean     0.121747    0.134799    0.178003    0.208259     ...        0.016069   \n",
      "std      0.061788    0.085152    0.118387    0.134416     ...        0.012008   \n",
      "min      0.003300    0.005500    0.007500    0.011300     ...        0.000000   \n",
      "25%      0.080900    0.080425    0.097025    0.111275     ...        0.008425   \n",
      "50%      0.106950    0.112100    0.152250    0.182400     ...        0.013900   \n",
      "75%      0.154000    0.169600    0.233425    0.268700     ...        0.020825   \n",
      "max      0.372900    0.459000    0.682800    0.710600     ...        0.100400   \n",
      "\n",
      "              V51         V52         V53         V54         V55         V56  \\\n",
      "count  208.000000  208.000000  208.000000  208.000000  208.000000  208.000000   \n",
      "mean     0.013420    0.010709    0.010941    0.009290    0.008222    0.007820   \n",
      "std      0.009634    0.007060    0.007301    0.007088    0.005736    0.005785   \n",
      "min      0.000800    0.000500    0.001000    0.000600    0.000400    0.000300   \n",
      "25%      0.007275    0.005075    0.005375    0.004150    0.004400    0.003700   \n",
      "50%      0.011400    0.009550    0.009300    0.007500    0.006850    0.005950   \n",
      "75%      0.016725    0.014900    0.014500    0.012100    0.010575    0.010425   \n",
      "max      0.070900    0.039000    0.035200    0.044700    0.039400    0.035500   \n",
      "\n",
      "              V57         V58         V59  \n",
      "count  208.000000  208.000000  208.000000  \n",
      "mean     0.007949    0.007941    0.006507  \n",
      "std      0.006470    0.006181    0.005031  \n",
      "min      0.000300    0.000100    0.000600  \n",
      "25%      0.003600    0.003675    0.003100  \n",
      "50%      0.005800    0.006400    0.005300  \n",
      "75%      0.010350    0.010325    0.008525  \n",
      "max      0.044000    0.036400    0.043900  \n",
      "\n",
      "[8 rows x 60 columns]\n"
     ]
    }
   ],
   "source": [
    "__author__ = 'mike_bowles'\n",
    "import pandas as pd\n",
    "from pandas import DataFrame\n",
    "import matplotlib.pyplot as plot\n",
    "target_url = (\"https://archive.ics.uci.edu/ml/machine-learning-\"\n",
    "\"databases/undocumented/connectionist-bench/sonar/sonar.all-data\")\n",
    "\n",
    "#read rocks versus mines data into pandas data frame\n",
    "rocksVMines = pd.read_csv(target_url,header=None, prefix=\"V\")\n",
    "\n",
    "#print head and tail of data frame\n",
    "print(rocksVMines.head())\n",
    "print(rocksVMines.tail())\n",
    "\n",
    "#print summary of data frame\n",
    "summary = rocksVMines.describe()\n",
    "print(summary)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### qqplotAttribute.py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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TY9ED4c034cYb4TOfgSFD4PDD4frri/wmWytkmovnJY0CIrsd54WkuYzMzDq8xsYHpC2P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\n8CrwkYhY3NQ2Kys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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fd61c9fed30>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "__author__ = 'ubuntu'\n",
    "import numpy as np\n",
    "import pylab\n",
    "import scipy.stats as stats\n",
    "import urllib.request, urllib.error, urllib.parse\n",
    "import sys\n",
    "\n",
    "target_url = (\"https://archive.ics.uci.edu/ml/machine-learning-\"\n",
    "\"databases/undocumented/connectionist-bench/sonar/sonar.all-data\")\n",
    "\n",
    "data = urllib.request.urlopen(target_url)\n",
    "\n",
    "#arrange data into list for labels and list of lists for attributes\n",
    "xList = []\n",
    "labels = []\n",
    "\n",
    "for line in data:\n",
    "    #split on comma\n",
    "    row = line.strip().decode().split(\",\")\n",
    "    xList.append(row)\n",
    "nrow = len(xList)\n",
    "ncol = len(xList[1])\n",
    "\n",
    "type = [0]*3\n",
    "colCounts = []\n",
    "\n",
    "#generate summary statistics for column 3 (e.g.)\n",
    "col = 3\n",
    "colData = []\n",
    "for row in xList:\n",
    "    colData.append(float(row[col]))\n",
    "\n",
    "\n",
    "stats.probplot(colData, dist=\"norm\", plot=pylab)\n",
    "pylab.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "### readPandas.py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Zz7R5HOMnF+IYyz985lpa97mDU7S8JEmoaTJm8GEoZUdejHKcjCORXSmQOMTa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\nRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fd61c9211d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "__author__ = 'mike_bowles'\n",
    "import pandas as pd\n",
    "from pandas import DataFrame\n",
    "import matplotlib.pyplot as plot\n",
    "target_url = \"https://archive.ics.uci.edu/ml/machine-learning-databases/undocumented/connectionist-bench/sonar/sonar.all-data\"\n",
    "\n",
    "#read rocks versus mines data into pandas data frame\n",
    "rocksVMines = pd.read_csv(target_url,header=None, prefix=\"V\")\n",
    "\n",
    "#calculate correlations between real-valued attributes\n",
    "\n",
    "corMat = DataFrame(rocksVMines.corr())\n",
    "\n",
    "#visualize correlations using heatmap\n",
    "plot.pcolor(corMat)\n",
    "plot.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### rockVmineContents.py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Col#\tNumber\tStrings\t Other\n",
      "0\t\t208\t\t0\t\t0\n",
      "1\t\t208\t\t0\t\t0\n",
      "2\t\t208\t\t0\t\t0\n",
      "3\t\t208\t\t0\t\t0\n",
      "4\t\t208\t\t0\t\t0\n",
      "5\t\t208\t\t0\t\t0\n",
      "6\t\t208\t\t0\t\t0\n",
      "7\t\t208\t\t0\t\t0\n",
      "8\t\t208\t\t0\t\t0\n",
      "9\t\t208\t\t0\t\t0\n",
      "10\t\t208\t\t0\t\t0\n",
      "11\t\t208\t\t0\t\t0\n",
      "12\t\t208\t\t0\t\t0\n",
      "13\t\t208\t\t0\t\t0\n",
      "14\t\t208\t\t0\t\t0\n",
      "15\t\t208\t\t0\t\t0\n",
      "16\t\t208\t\t0\t\t0\n",
      "17\t\t208\t\t0\t\t0\n",
      "18\t\t208\t\t0\t\t0\n",
      "19\t\t208\t\t0\t\t0\n",
      "20\t\t208\t\t0\t\t0\n",
      "21\t\t208\t\t0\t\t0\n",
      "22\t\t208\t\t0\t\t0\n",
      "23\t\t208\t\t0\t\t0\n",
      "24\t\t208\t\t0\t\t0\n",
      "25\t\t208\t\t0\t\t0\n",
      "26\t\t208\t\t0\t\t0\n",
      "27\t\t208\t\t0\t\t0\n",
      "28\t\t208\t\t0\t\t0\n",
      "29\t\t208\t\t0\t\t0\n",
      "30\t\t208\t\t0\t\t0\n",
      "31\t\t208\t\t0\t\t0\n",
      "32\t\t208\t\t0\t\t0\n",
      "33\t\t208\t\t0\t\t0\n",
      "34\t\t208\t\t0\t\t0\n",
      "35\t\t208\t\t0\t\t0\n",
      "36\t\t208\t\t0\t\t0\n",
      "37\t\t208\t\t0\t\t0\n",
      "38\t\t208\t\t0\t\t0\n",
      "39\t\t208\t\t0\t\t0\n",
      "40\t\t208\t\t0\t\t0\n",
      "41\t\t208\t\t0\t\t0\n",
      "42\t\t208\t\t0\t\t0\n",
      "43\t\t208\t\t0\t\t0\n",
      "44\t\t208\t\t0\t\t0\n",
      "45\t\t208\t\t0\t\t0\n",
      "46\t\t208\t\t0\t\t0\n",
      "47\t\t208\t\t0\t\t0\n",
      "48\t\t208\t\t0\t\t0\n",
      "49\t\t208\t\t0\t\t0\n",
      "50\t\t208\t\t0\t\t0\n",
      "51\t\t208\t\t0\t\t0\n",
      "52\t\t208\t\t0\t\t0\n",
      "53\t\t208\t\t0\t\t0\n",
      "54\t\t208\t\t0\t\t0\n",
      "55\t\t208\t\t0\t\t0\n",
      "56\t\t208\t\t0\t\t0\n",
      "57\t\t208\t\t0\t\t0\n",
      "58\t\t208\t\t0\t\t0\n",
      "59\t\t208\t\t0\t\t0\n",
      "60\t\t0\t\t208\t\t0\n"
     ]
    }
   ],
   "source": [
    "__author__ = 'mike_bowles'\n",
    "import urllib.request, urllib.error, urllib.parse\n",
    "import sys\n",
    "\n",
    "#read data from uci data repository\n",
    "target_url = (\"https://archive.ics.uci.edu/ml/machine-learning-\"\n",
    "\"databases/undocumented/connectionist-bench/sonar/sonar.all-data\")\n",
    "\n",
    "data = urllib.request.urlopen(target_url)\n",
    "\n",
    "#arrange data into list for labels and list of lists for attributes\n",
    "xList = []\n",
    "labels = []\n",
    "\n",
    "for line in data:\n",
    "    #split on comma\n",
    "    row = line.strip().decode().split(\",\")\n",
    "    xList.append(row)\n",
    "nrow = len(xList)\n",
    "ncol = len(xList[1])\n",
    "\n",
    "type = [0]*3\n",
    "colCounts = []\n",
    "\n",
    "for col in range(ncol):\n",
    "    for row in xList:\n",
    "        try:\n",
    "            a = float(row[col])\n",
    "            if isinstance(a, float):\n",
    "                type[0] += 1\n",
    "        except ValueError:\n",
    "            if len(row[col]) > 0:\n",
    "                type[1] += 1\n",
    "            else:\n",
    "                type[2] += 1\n",
    "\n",
    "    colCounts.append(type)\n",
    "    type = [0]*3\n",
    "\n",
    "sys.stdout.write(\"Col#\" + '\\t' + \"Number\" + '\\t' +\n",
    "                 \"Strings\" + '\\t ' + \"Other\\n\")\n",
    "iCol = 0\n",
    "for types in colCounts:\n",
    "    sys.stdout.write(str(iCol) + '\\t\\t' + str(types[0]) + '\\t\\t' +\n",
    "                     str(types[1]) + '\\t\\t' + str(types[2]) + \"\\n\")\n",
    "    iCol += 1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### rockVmineSummaries.py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of Rows of Data = 208\n",
      "Number of Columns of Data = 61"
     ]
    }
   ],
   "source": [
    "__author__ = 'mike_bowles'\n",
    "import urllib.request, urllib.error, urllib.parse\n",
    "import sys\n",
    "\n",
    "#read data from uci data repository\n",
    "target_url = (\"https://archive.ics.uci.edu/ml/machine-learning-\"\n",
    "\"databases/undocumented/connectionist-bench/sonar/sonar.all-data\")\n",
    "\n",
    "data = urllib.request.urlopen(target_url)\n",
    "\n",
    "#arrange data into list for labels and list of lists for attributes\n",
    "xList = []\n",
    "labels = []\n",
    "for line in data:\n",
    "    #split on comma\n",
    "    row = line.strip().decode().split(\",\")\n",
    "    xList.append(row)\n",
    "\n",
    "sys.stdout.write(\"Number of Rows of Data = \" + str(len(xList)) + '\\n')\n",
    "sys.stdout.write(\"Number of Columns of Data = \" + str(len(xList[1])))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### rVMSummaryStats.py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mean = \t0.0538923076923\t\tStandard Deviation = \t 0.0464159832226\n",
      "\n",
      "Boundaries for 4 Equal Percentiles \n",
      "[0.0057999999999999996, 0.024375000000000001, 0.044049999999999999, 0.064500000000000002, 0.4264]\n",
      " \n",
      "Boundaries for 10 Equal Percentiles \n",
      "[0.0057999999999999996, 0.0141, 0.022740000000000003, 0.027869999999999995, 0.036220000000000002, 0.044049999999999999, 0.050719999999999987, 0.059959999999999986, 0.077940000000000009, 0.10836, 0.4264]\n",
      " \n",
      "Unique Label Values \n",
      "{'R', 'M'}\n",
      "\n",
      "Counts for Each Value of Categorical Label \n",
      "['R', 'M']\n",
      "[97, 111]\n"
     ]
    }
   ],
   "source": [
    "__author__ = 'mike_bowles'\n",
    "import urllib.request, urllib.error, urllib.parse\n",
    "import sys\n",
    "import numpy as np\n",
    "\n",
    "#read data from uci data repository\n",
    "target_url = (\"https://archive.ics.uci.edu/ml/machine-learning-\"\n",
    "\"databases/undocumented/connectionist-bench/sonar/sonar.all-data\")\n",
    "\n",
    "data = urllib.request.urlopen(target_url)\n",
    "\n",
    "#arrange data into list for labels and list of lists for attributes\n",
    "xList = []\n",
    "labels = []\n",
    "\n",
    "for line in data:\n",
    "    #split on comma\n",
    "    row = line.strip().decode().split(\",\")\n",
    "    xList.append(row)\n",
    "nrow = len(xList)\n",
    "ncol = len(xList[1])\n",
    "\n",
    "type = [0]*3\n",
    "colCounts = []\n",
    "\n",
    "#generate summary statistics for column 3 (e.g.)\n",
    "col = 3\n",
    "colData = []\n",
    "for row in xList:\n",
    "    colData.append(float(row[col]))\n",
    "\n",
    "colArray = np.array(colData)\n",
    "colMean = np.mean(colArray)\n",
    "colsd = np.std(colArray)\n",
    "sys.stdout.write(\"Mean = \" + '\\t' + str(colMean) + '\\t\\t' +\n",
    "            \"Standard Deviation = \" + '\\t ' + str(colsd) + \"\\n\")\n",
    "\n",
    "\n",
    "#calculate quantile boundaries\n",
    "ntiles = 4\n",
    "\n",
    "percentBdry = []\n",
    "\n",
    "for i in range(ntiles+1):\n",
    "    percentBdry.append(np.percentile(colArray, i*(100)/ntiles))\n",
    "\n",
    "sys.stdout.write(\"\\nBoundaries for 4 Equal Percentiles \\n\")\n",
    "print(percentBdry)\n",
    "sys.stdout.write(\" \\n\")\n",
    "\n",
    "\n",
    "#run again with 10 equal intervals\n",
    "ntiles = 10\n",
    "\n",
    "percentBdry = []\n",
    "\n",
    "for i in range(ntiles+1):\n",
    "    percentBdry.append(np.percentile(colArray, i*(100)/ntiles))\n",
    "\n",
    "sys.stdout.write(\"Boundaries for 10 Equal Percentiles \\n\")\n",
    "print(percentBdry)\n",
    "sys.stdout.write(\" \\n\")\n",
    "\n",
    "\n",
    "#The last column contains categorical variables\n",
    "\n",
    "col = 60\n",
    "colData = []\n",
    "for row in xList:\n",
    "    colData.append(row[col])\n",
    "\n",
    "unique = set(colData)\n",
    "sys.stdout.write(\"Unique Label Values \\n\")\n",
    "print(unique)\n",
    "\n",
    "#count up the number of elements having each value\n",
    "\n",
    "catDict = dict(zip(list(unique),range(len(unique))))\n",
    "\n",
    "catCount = [0]*2\n",
    "\n",
    "for elt in colData:\n",
    "    catCount[catDict[elt]] += 1\n",
    "\n",
    "sys.stdout.write(\"\\nCounts for Each Value of Categorical Label \\n\")\n",
    "print(list(unique))\n",
    "print(catCount)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### sampleCorrHeatMap.py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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QhNUig5UKbWN9r8JQ6ThUMZainMkDrRqXZXqk89tClmlnxBUy5XXPr79Ey5kE890eH/iP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\nRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fd61ca152e8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "__author__ = 'mike_bowles'\n",
    "import pandas as pd\n",
    "from pandas import DataFrame\n",
    "import matplotlib.pyplot as plot\n",
    "target_url = (\"https://archive.ics.uci.edu/ml/machine-learning-\"\n",
    "\"databases/undocumented/connectionist-bench/sonar/sonar.all-data\")\n",
    "\n",
    "#read rocks versus mines data into pandas data frame\n",
    "rocksVMines = pd.read_csv(target_url,header=None, prefix=\"V\")\n",
    "\n",
    "#calculate correlations between real-valued attributes\n",
    "\n",
    "corMat = DataFrame(rocksVMines.corr())\n",
    "\n",
    "#visualize correlations using heatmap\n",
    "plot.pcolor(corMat)\n",
    "plot.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### targetCorr.py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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otHyzenykYBPVlSRPojotvRvqPOCHwK8APyW5ffaw6vfNLJN0Qpp4LiK5a+eP\ngMVKnu89nfQOnTXa3wRcKOmXACRNk3RmneWsITm19AvpfPDzL/gfp9ci6o02epzkFBjAW3PlG4B3\nDV+HSO+Oa1aYk4JNVCuAe6rKvkIy6mgrcFTSw+ldNDeSfKF/T9JVBdr+LvA1ki/qj0TEvojYTXL/\n/q3AF0mehzxsNfB1SRsjYj/Jw33WSNqatvESavtnkovUXxq+w2f6UJzPAdtIboe9uc68fwh8UtK3\nSO6KOuwjJHfX3KrkIfAfKdBfs4zvkmpmZhkfKZiZWcZJwczMMk4KZmaWcVIwM7OMk4KZmWWcFMzM\nLOOkYGZmGScFMzPL/H9cvMue6Lr3JgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fd5f96f27f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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BVcen7YVqr4VICS8viBJlEPcyigvW4o6rccWvYagVg4COIF91J2GAgVitbZDK\nxZQxRZKxNF9zmKs5ifvDDw2artrrYCRvs1B3+dKZqzx8cHhNE7yxgkqjjS3Jcs5iueUnAdPetMK5\najvpcSTE+i0M8hmTHzw2xo2qs6ZuIJ0BIyPJkX2FxGIdFLTt507ot0lPvHPe5eUW11baBFJiCUEo\n4UbdTYoAVQDdwPGVq+/IWIGrlXZXmnN6E6b0vsO7nXa6Hm0v5AtPX6KYsTg+UeJGzVH3koRQRpxf\naDJRznJsf7Hv75beXjMm3mLzdgZ3b2ZVux2/x61ubbuXaij2hiNzFxkUkOq9uY+OFZitqeyYdEfP\nqqMCteWcpdIl4xYUq94EMqYgYxo4fkTLVctaISV+BHNVF8tQLh3DUMHkWLCEkey06RadTXqk2o5T\nSPyOIM51CsAMIfDCqLMqUO/PZUwcP0oMWC+UDOVWg7srbY+6o1YYlqmEnG0ZyV4H8W5vSw2vqwne\n33/nffzrJ1/jq6/Or2kJ8c77x/j777wvsQLTcZu/fHmOP31hhgPD+cQVMQgJfODUBN88t7gmpdAy\nDd4yPcx3r6500npNrlVa6wZt+7kT+u0KFkaSpYZH2w8xBJio/bFlJMlZapMlCJCp7y1kp1HiaI6Z\niurBlCa97/BeSDtdj9hAOrJPCckHDpTXVHi/fqPO3IrD8fHuJnVep09WsSd9u3eLze0M7g4SqDe7\nqt3qOG6lDmKv1lDszTvzNtLPgux3c1umwXAuw8OHhqi0VDVnPmMyu+J0LHB147e9IGkTnRYccdZP\n2u8fvxqmagoA/EiSNw2kUEVnYSRxU+8JI7BMZZlHUq1Mxss2iw1PxSU6QVir40eKC9mylsFYMUu9\ns9+B60ed1YjRUQzqGsR9hhw/REo4Nl5MJrEhBF94+hJ+JPnhN01Sd4Nkn4Ny1qLS9vnC05fWuAeK\nWYsfeXg/T11YYl/RHmi9+WHEYt2l0lI9qD7x2FG+dnahbwHTx99xhPefnGC26vTNYd+oqrjfrmDL\nTRc/jLCMDNmMctmprq5m0jqk4YYEYYjoKN5S1qLS8pI6jd7MKqvjStwraaeD6Gcg9avwPj5R5Kuv\nNmm5QVcbikrLS7bXhLX7jcRsR3B3PYH6lsPDnJwss7+cI2MKLi81OTSSv+Wq6JjVdGaPP3/xBm0v\nYKKUXS18NNVcWM9VtpdrKO55pdDPguy9udMIBJOlLNcrbYbyGdpeRNNThVnxrmxI5aqJd+vKZ0wk\nqpdS/JFRp6gs3QBPJucAPwwJIuXiMQWYptHZnzmi3KkSbjgqJuGFEV4gk9TWuZpDEEraqFbaTS9k\nvJRlrGDT7OyRXGv7qv8RKiiAe7mtAAAgAElEQVSt4ghrr4+gexK/MV/vcrUVslayU1ml7WMZgkuL\nzb7ugfWst979eCeHbL505kpiNf3TH3lgoPDP2+ZqY76FJlPDOb52dmFTVcVpV1TeMjs734lO3Ybo\nFMmpa+/6SqmYQtIKJeO2yWQ5R6OjGNN1GjMVJ6mAbnkhEd6eSTsdxGYzdvKd9i4XFptJp2CI60ZW\nj+vdYjPNrQR3BwnUIIx47Uadz3/9AoWMyampEkiVIny96jA1nCVjbD0NeG06c5MbVVc1ZUS5XNPx\nl+nRHJeiqO9c2Ms1FPe8UugXkOq9udPES+jY7RDvWTBWtKm2fIKO397p7IQWdYLEbhASoQS8gCSl\n0mC1b1GM7Fg8WQF+FFGyLfJZC4Gk7gQIISjnTFZaSpiVs1ZSCzFRyibtGoSAYtbA8VRltRtEPLC/\nhGUYzNdN8EL8UGXU5FOrIilVHUXaChYod1Pakhy0UxkSrlcd3n9ygvEet1y/njZx7UK8XeOB4VxS\nE7Ce1dS/pUTEG3NqD4y3Hxnp6qVUaXm8fL3ObNXhoYPDTJSy2NZqMda5+QZtP2Q4ryqugyhiXzHL\nvqLaqCjeH9sQgsWGizBE197QsFqncXyizBtzdR48OJSk9O5Vl1HMzWTsTHcyxtLbblqdXfHSSQTp\nLTbT3Epwt59ATde/xEWILTfkwakSh0ZyXF9pk1tnB76N6FVEkYSXrtfUKj5Wbi4cHM4nsaSZSpui\nbfHtc4tdrrK9XkOxt+/S20C/gFR8c6dJL4XTbgdDwIGhrNpvOGOQMQyEWO0smrXMjqtG7Z/Q2SYm\nIc67FyJKup12YsQUcpbKNuoIR7VKyCCFEsjDOYuGF+KHEi+MmK+7rHRy+R+7f4wTk6qK1g1Criy1\nuLTU5PkrK2QzZrKhThzA9oIwcYEhYChnMVbMdgLmyu21WPcSS7Iry6TPTmVzVYdf/+obfOYjD3UJ\n8n49bS4vtViouxSzFtNjua7g8yCraZC1+OpslSiSNL2AF2aqnD46ikTFiOZrLkGkzldpeowWs0yP\nqvOdnCypamkkbz08giEMXrpepZxd/W7piemHEtNQitKgO/spCCMWGi6PTg/fES0UYnfI+YUGlabP\nZDlat0ARlBL86dOHubzcSn7HMIySRIJ0u/FebiW4O0ig9ta/9PZmOrKvyLWVNjfqLu85OXHT5+1V\nRHM1h2rbx+8YT6BctEtNj4lyFsMQXSnOaVfZXq+huOeVQj+XxmjBVu2ao94tAQtdbodKU+2r8M5j\nY7wyW1d57ygffSghY6iCMzeIsAwDQbTaxjSFYQhsQ/mvo04rVNHZNCeMIuqOh8DAMMASYbLBTBCp\n/4tZEyswEEIyPZrnPcfHE19vMWvhhxHXVxzGS1mcQG0lWrRVBerl5ZZKExWCfSXVBTOfMdfk/Vum\nwb6ynSjLflkm6e9TsE1mV/ovf9PB55evV/mtv73A/eNFxjuWez96raZ+1mIcCyp3guk1x+e1G3Vq\nbZ/Fhks2YzBZVoqu2g4ohSGv32hwdbnNQweHePt9Y+xbbHF4rACoNN10vKHrOwp4+OAwl5aaCCGS\nivi9VqG8Hr0rrSBS9QfXVtocGVNCXcKaQHPsUnxwaojT9411FX/ef26RS4vNJFDdj1sJ7vYTqP3q\nXwxDzZ94HxDYuuXdTxE5fkjLCyimfl/bNLq6F4BSTgsNt2ufj71eQ3HPKwVY69KwrdVMkngv5t6l\nsGWqqt8TkyVafsSB4Sx+EDLfcFV6Z2enNT9SGT+x9SpTCkFKknRSUJ1G3SBCoILSdUeltWYsQdZe\nbWkdu3cylqCYzXBsoqTy9Q3Bw1NDayyQWICPFOxON9iAbEfwD+eVNSNRQnWivGrxxjUAfhjx3uMT\njObtzg50/bNMepncYBIWsxb5jNXZ03pwhkh8vdOb+/SzFntjQfmMyXNXlpGRWo3VXRIXVy5jcGSs\nyFjRZrnp8fajo3zsLYf4V3/2SmLJpuMN6dVQnHHlhxHvOTHOJx47OjDesVcZtNJqeSFXltpcWW5y\nbr6RxMVijSc6RshPvW06+Y7p3kQPHxxeN4B6q8H2vjHAPptmxaT3Admq5d1PEam91dX1iIntPccP\nk2ujlJNaZcfs9RqKvX3n3ib6uTQKttoqcqHhcnyi1LV3QHxzH91X5FPvO04kZWIp/c1r87x8vcpo\n0eaNuQZBGDGUU03dzE6WTxipArOkZQNxVpEK+EYmZAzRyYIRDOUtTCO10YtQhVRup4W0qjz1KdrG\nGoXQK8CNTkFcrAz2FW3cIMTxQ2rtgLGiTKycuuNTzme4b7zI449MdfoOGSw23IGBeFh1tY2Xs8zV\nnHUn4VaspkHL73QsKIwks9U2TSdkKK+2Q42RUll/s9U2bzpQZrKc5XszVT72lkNdq8Z087f0jmwt\nL2T/cI73nppIVgO9sZO9zqBA54nJMpWmz8WlJp4fsq+UTbKPokhSd3yarmrj0e6kA6fZrpbXgxgY\nAxxwD/WueLdiefe7Rwu2iUAkmX5popThF3Xm+njK2LrdNRQ3i1YKHfr1QZISzs7X+d5MlRu19d0D\n/Syl9xzfx6WlJjMVVQBkCAhDtQzPGIIIki05483mDUMphIYXMlxQfXcabki/eydjCNpeSMsPOXWg\nxFynyjbNoEyqqZEcckW5SA4M5ai0fJaarnKzWKqmopSz+Dtvm+Yn33Io+Z6PHRvjz753fV1LJ+1q\n22gSbsVqGqRI0rGg5aZL2wuVEuyZtbEybnth0oYitiD7BcLjHdkW6y7zdZepkTy/9KFTd5wiiNlo\nz4ShfCbpL7Xc9LA7cTEhBEf2FTgxWWau5g7MjLnVltfrMTAG2HMPDap034rl3e8ezWXMzl4h0Zo2\nMukNqhpewHgpy0h+dRy3q4Ziq2il0ENvm94fvH+Mj70l2PTN3WsplXMZTk2a1Fy1Jedy02WkYFPO\nZXC8kJW2T8sPMVDWbRDC/nKOgh2SzRiUshn8sN3ZpKdbwHlhhGmonj0fODXJHz97Zc14BmVS5Syz\nK30yaxmq0V/JZjhv8+bpYX72saN9s4fOXFrmYqfT56BN7mNX20aTcCtW04WFZt/vFMeC/DCi5qiV\nGTJaoz869YCMFuykDUWsvDaydH/iLQf3fKxgI9YLdPphxGzVYXokr5ILGsrdM1HOdhUcbsY/v9WW\n1+vRNwbYpwixt6cWbN3y7nePjhZshvIZam0vtYGWMjhyGTOZCyXb4si+4ppzbvfOctuJVgqb4GZv\n7kGW0tRwjt/79kWeubhMo5P9M5zPUM5auFFEzjJ5dHqYH31oP//pxevMrqj9GvaXc0n1sURVOfuh\ncjUdHsvzkUcP8NDBob7CtTeTqjeLKk6frLQ8ZqttfvIt0/zIw/vXVXq/9KEHOL/wXeqO3yWc12xy\nv4lJuBWraZAiiWNBZ+caQGdZL1jrUgsjhnIWGcug7YfKJ82q8tpJS3cvsJ7Lrtc/n8+YjBXtJFgb\ns5vdRXsFau+OcP16asHWLe9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T5G1zt4d5R7Gb1/RWBdu9eD9s53fWiuXOQ/86KdpeyOe+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\nRK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fd5f943f0f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "__author__ = 'mike_bowles'\n",
    "import pandas as pd\n",
    "from pandas import DataFrame\n",
    "import matplotlib.pyplot as plot\n",
    "from random import uniform\n",
    "target_url = (\"https://archive.ics.uci.edu/ml/machine-learning-\"\n",
    "\"databases/undocumented/connectionist-bench/sonar/sonar.all-data\")\n",
    "\n",
    "#read rocks versus mines data into pandas data frame\n",
    "rocksVMines = pd.read_csv(target_url,header=None, prefix=\"V\")\n",
    "\n",
    "#change the targets to numeric values\n",
    "target = []\n",
    "for i in range(208):\n",
    "    #assign 0 or 1 target value based on \"M\" or \"R\" labels\n",
    "    if rocksVMines.iat[i,60] == \"M\":\n",
    "        target.append(1.0)\n",
    "    else:\n",
    "        target.append(0.0)\n",
    "\n",
    "    #plot rows of data as if they were series data\n",
    "dataRow = rocksVMines.iloc[0:208,35]\n",
    "plot.scatter(dataRow, target)\n",
    "\n",
    "plot.xlabel(\"Attribute Value\")\n",
    "plot.ylabel(\"Target Value\")\n",
    "plot.show()\n",
    "\n",
    "#\n",
    "#To improve the visualization, this version dithers the points a little\n",
    "# and makes them somewhat transparent\n",
    "target = []\n",
    "for i in range(208):\n",
    "    #assign 0 or 1 target value based on \"M\" or \"R\" labels\n",
    "    # and add some dither\n",
    "    if rocksVMines.iat[i,60] == \"M\":\n",
    "        target.append(1.0 + uniform(-0.1, 0.1))\n",
    "    else:\n",
    "        target.append(0.0 + uniform(-0.1, 0.1))\n",
    "\n",
    "    #plot rows of data as if they were series data\n",
    "dataRow = rocksVMines.iloc[0:208,35]\n",
    "plot.scatter(dataRow, target, alpha=0.5, s=120)\n",
    "\n",
    "plot.xlabel(\"Attribute Value\")\n",
    "plot.ylabel(\"Target Value\")\n",
    "plot.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### wineCorrHeatMap.py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fd618281f60>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "__author__ = 'mike_bowles'\n",
    "import pandas as pd\n",
    "from pandas import DataFrame\n",
    "from pylab import *\n",
    "import matplotlib.pyplot as plot\n",
    "from math import exp\n",
    "\n",
    "target_url = (\"http://archive.ics.uci.edu/ml/machine-\"\n",
    "              \"learning-databases/wine-quality/winequality-red.csv\")\n",
    "wine = pd.read_csv(target_url,header=0, sep=\";\")\n",
    "wineCols = len(wine.columns)\n",
    "\n",
    "#calculate correlation matrix\n",
    "corMat = DataFrame(wine.corr())\n",
    "\n",
    "#visualize correlations using heatmap\n",
    "plot.pcolor(corMat)\n",
    "plot.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### wineParallelPlot.py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['fixed acidity', 'volatile acidity', 'citric acid', 'residual sugar',\n",
      "       'chlorides', 'free sulfur dioxide', 'total sulfur dioxide', 'density',\n",
      "       'pH', 'sulphates', 'alcohol', 'quality'],\n",
      "      dtype='object')\n"
     ]
    },
    {
     "data": {
      "image/png": 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Gy2I/p6o/cdkmygtU9c9u68iM2cUWOkOyXF+VzF9rTDkR+ogUHYsTp5TFIS//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\n1K60NfUEQOHUdbFEbYc5nuthpAtSYYWDPX5FyONPrs+7vkoCK+ptd45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MlPQS8Ed8lJjl\nd8BlZnZGvGi7Sv6V1zPAu3N+TwB+K+mECNdefj0raQxwaWZ56zS8YbpWUm98pHFSXBsB/EzSijg+\nNfLzaeARfKq/EP9QADN7UtL38KXGp/Cpekem/2V5V4Vz8TxdgI8Ix5jZyzE77QoGA+fJE1gHb5B/\nZ2Ym6TDgXEnfjGt/AL4e4Y4H3gJ8M64DjDCzZ8oSMrPnJd0R5fIG4F7alvHngVdimaMZeL677MvZ\nWlZHRoc9p+Hv4y6LeyhjOHCqpJXAMuCYKul3gr8Cx0o6H1iMf+RTNmhcE3YHJsQMciXwefxdx68k\nfR2vM2U8gC8nbQEcZ2Yrysq1mc2XNBf/GONhfPBZxI3AcZLujfhn5eIpqodj8Hd2kySdCjyLv5dt\nj3bb5HqkX+gnViOpn5kti5nL1cAkM8t3nolEjxMN3FTzT7Vfk8Sy1lQzu7KnbekJXne/c0l0KePk\nL20X4rOba3rYnkQi8TolzVwSiUQi0XDSzCWRSCQSDSd1LolEIpFoOKlzSSQSiUTDSZ1LYq1B0mGS\nLL79r53LKw4PkVT6q225TtTZ4e6wKrCkE9VBjSt1UJU2wnRKATeR6C5S55JYm6j9kO5jmXNNtFYc\nLpUEkfQGM7vbzMaugQ0n4soRicT/NalzSawVhFLBMFyePtu5ZBWHvwJ8B//V8Ty5uu04ZRSTJQ2X\nNDUT/q2S/iRXr/1spNXKj6Rz5ArOY3EB0FvkCtJIGqECJet27mOJpNPD/wK1KBBvKmmaXDX6fDLS\nHJI+LumuuKfz4xfVg8LmN8UvxG+TNKI04USiwaTOJbG28BHgRjN7EHhBUk1y5KvAbSFkOB5Xkr48\nji8PP3sDHzazo9tGyx64Rta+wLeU2ygui5mdjasbHGRmB8Wy1WnAIWa2F3A3cHKFe3ku/J+Ha00B\nfBu43cz2xAUltwWQC1oehasDD8HVKUab2aO4eOVEXKV4kZl1aNuCRGJN6EnhykSikYwCfhrumjr1\nnIphVysmF3BtXHspZiP7AFU3n8sqWQO8Edecq0dNtuge4PBwH1Bzm9n1kmqq3+/CO8fZkUYfXGoI\nM7tQrgl2HKE5l0h0F6lzSbzukQv0HQzsJsnw/SdM0pcrRtGe8nKRqm2ZsnQb0yhRsq5DTaF2Fa3r\naJnc/q/N7GttLviHBdvEYT9chy6R6BbSslhibWAkcLGZDQp16oG4fM1+5BSHC47r8WH5Tpmb4oKM\ns3FRx10krSdpI3z2UBR/oZJ1x28PaK0c/T6gpvo9HRgpafO4tolclRh8WWwyvhR4QSfTTSQ6Repc\nEmsDoyhWpz4aVyF+Rb7d60nALXjHME/Vtm29C1clngWcYWZPmdnj+AZx9+KNd1b9+ZfADZJuMbNn\ncTXaS0PBdhYtm0V1lNPxrWjn4IrXjwHE5k6nAdMijZuArSQdiG/sNN7MJgP/lVRPBTeRaBhJWyyR\nSCQSDSfNXBKJRCLRcFLnkkgkEomGkzqXRCKRSDSc1LkkEolEouGkziWRSCQSDSd1LolEIpFoOKlz\nSSQSiUTDSZ1LIpFIJBrO/wCOICC3Ob5ZkAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fd5f9530978>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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3QGls7Mj7aa1xr36AeD7BBcyTHMWR/DngQyAEfh1oAv/WMZx7HpgXke/2f/4N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\nSpSuHQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fd5f8a0a5f8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "__author__ = 'mike_bowles'\n",
    "import pandas as pd\n",
    "from pandas import DataFrame\n",
    "from pylab import *\n",
    "import matplotlib.pyplot as plot\n",
    "from math import exp\n",
    "\n",
    "target_url = (\"http://archive.ics.uci.edu/ml/machine-\"\n",
    " \"learning-databases/wine-quality/winequality-red.csv\")\n",
    "\n",
    "wine = pd.read_csv(target_url,header=0, sep=\";\")\n",
    "\n",
    "#print column names in order to have the full versions\n",
    "print(wine.columns)\n",
    "\n",
    "#change column names to shorter ones to fit graph\n",
    "wine.columns = ['fixAcid', 'volAcid', 'citAcid',\n",
    "    'resSugr', 'chlor', 'frSO2', 'totSO2',\n",
    "    'dens', 'pH', 'sulpha', 'alcohol', 'quality']\n",
    "\n",
    "#generate statistical summaries\n",
    "summary = wine.describe()\n",
    "nrows = len(wine.index)\n",
    "tasteCol = len(summary.columns)\n",
    "meanTaste = summary.iloc[1,tasteCol - 1]\n",
    "sdTaste = summary.iloc[2,tasteCol - 1]\n",
    "nDataCol = len(wine.columns) -1\n",
    "\n",
    "for i in range(nrows):\n",
    "    #plot rows of data as if they were series data\n",
    "    dataRow = wine.iloc[i,1:nDataCol]\n",
    "    normTarget = (wine.iloc[i,nDataCol] - meanTaste)/sdTaste\n",
    "    labelColor = 1.0/(1.0 + exp(-normTarget))\n",
    "    dataRow.plot(color=plot.cm.RdYlBu(labelColor), alpha=0.5)\n",
    "\n",
    "plot.xlabel(\"Attribute Index\")\n",
    "plot.ylabel((\"Attribute Values\"))\n",
    "plot.show()\n",
    "\n",
    "wineNormalized = wine\n",
    "ncols = len(wineNormalized.columns)\n",
    "\n",
    "for i in range(ncols):\n",
    "    mean = summary.iloc[1, i]\n",
    "    sd = summary.iloc[2, i]\n",
    "    wineNormalized.iloc[:,i:(i + 1)] = \\\n",
    "        (wineNormalized.iloc[:,i:(i + 1)] - mean) / sd\n",
    "\n",
    "#Try again with normalized values\n",
    "for i in range(nrows):\n",
    "    #plot rows of data as if they were series data\n",
    "    dataRow = wineNormalized.iloc[i,1:nDataCol]\n",
    "    normTarget = wineNormalized.iloc[i,nDataCol]\n",
    "    labelColor = 1.0/(1.0 + exp(-normTarget))\n",
    "    dataRow.plot(color=plot.cm.RdYlBu(labelColor), alpha=0.5)\n",
    "\n",
    "plot.xlabel(\"Attribute Index\")\n",
    "plot.ylabel((\"Attribute Values\"))\n",
    "plot.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### wineSummary.py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   fixed acidity  volatile acidity  citric acid  residual sugar  chlorides  \\\n",
      "0            7.4              0.70         0.00             1.9      0.076   \n",
      "1            7.8              0.88         0.00             2.6      0.098   \n",
      "2            7.8              0.76         0.04             2.3      0.092   \n",
      "3           11.2              0.28         0.56             1.9      0.075   \n",
      "4            7.4              0.70         0.00             1.9      0.076   \n",
      "\n",
      "   free sulfur dioxide  total sulfur dioxide  density    pH  sulphates  \\\n",
      "0                 11.0                  34.0   0.9978  3.51       0.56   \n",
      "1                 25.0                  67.0   0.9968  3.20       0.68   \n",
      "2                 15.0                  54.0   0.9970  3.26       0.65   \n",
      "3                 17.0                  60.0   0.9980  3.16       0.58   \n",
      "4                 11.0                  34.0   0.9978  3.51       0.56   \n",
      "\n",
      "   alcohol  quality  \n",
      "0      9.4        5  \n",
      "1      9.8        5  \n",
      "2      9.8        5  \n",
      "3      9.8        6  \n",
      "4      9.4        5  \n",
      "       fixed acidity  volatile acidity  citric acid  residual sugar  \\\n",
      "count    1599.000000       1599.000000  1599.000000     1599.000000   \n",
      "mean        8.319637          0.527821     0.270976        2.538806   \n",
      "std         1.741096          0.179060     0.194801        1.409928   \n",
      "min         4.600000          0.120000     0.000000        0.900000   \n",
      "25%         7.100000          0.390000     0.090000        1.900000   \n",
      "50%         7.900000          0.520000     0.260000        2.200000   \n",
      "75%         9.200000          0.640000     0.420000        2.600000   \n",
      "max        15.900000          1.580000     1.000000       15.500000   \n",
      "\n",
      "         chlorides  free sulfur dioxide  total sulfur dioxide      density  \\\n",
      "count  1599.000000          1599.000000           1599.000000  1599.000000   \n",
      "mean      0.087467            15.874922             46.467792     0.996747   \n",
      "std       0.047065            10.460157             32.895324     0.001887   \n",
      "min       0.012000             1.000000              6.000000     0.990070   \n",
      "25%       0.070000             7.000000             22.000000     0.995600   \n",
      "50%       0.079000            14.000000             38.000000     0.996750   \n",
      "75%       0.090000            21.000000             62.000000     0.997835   \n",
      "max       0.611000            72.000000            289.000000     1.003690   \n",
      "\n",
      "                pH    sulphates      alcohol      quality  \n",
      "count  1599.000000  1599.000000  1599.000000  1599.000000  \n",
      "mean      3.311113     0.658149    10.422983     5.636023  \n",
      "std       0.154386     0.169507     1.065668     0.807569  \n",
      "min       2.740000     0.330000     8.400000     3.000000  \n",
      "25%       3.210000     0.550000     9.500000     5.000000  \n",
      "50%       3.310000     0.620000    10.200000     6.000000  \n",
      "75%       3.400000     0.730000    11.100000     6.000000  \n",
      "max       4.010000     2.000000    14.900000     8.000000  \n"
     ]
    },
    {
     "data": {
      "image/png": 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vZ/Xq1Zw6dYrVq1ezfv16p0frp06d4vXXX6ejo4PXX3+dU6dOOYtlMldjYyPLly8nEomg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\nPJYQjDHGAPD/AT5LgmIMyuduAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fd5f9530208>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "__author__ = 'mike_bowles'\n",
    "import pandas as pd\n",
    "from pandas import DataFrame\n",
    "from pylab import *\n",
    "import matplotlib.pyplot as plot\n",
    "\n",
    "target_url = (\"http://archive.ics.uci.edu/ml/machine-\"\n",
    " \"learning-databases/wine-quality/winequality-red.csv\")\n",
    "\n",
    "wine = pd.read_csv(target_url,header=0, sep=\";\")\n",
    "\n",
    "print(wine.head())\n",
    "\n",
    "#generate statistical summaries\n",
    "summary = wine.describe()\n",
    "print(summary)\n",
    "\n",
    "wineNormalized = wine\n",
    "ncols = len(wineNormalized.columns)\n",
    "\n",
    "for i in range(ncols):\n",
    "    mean = summary.iloc[1, i]\n",
    "    sd = summary.iloc[2, i]\n",
    "    wineNormalized.iloc[:,i:(i + 1)] = \\\n",
    "        (wineNormalized.iloc[:,i:(i + 1)] - mean) / sd\n",
    "\n",
    "array = wineNormalized.values\n",
    "boxplot(array)\n",
    "plot.xlabel(\"Attribute Index\")\n",
    "plot.ylabel((\"Quartile Ranges - Normalized \"))\n",
    "show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
